a case series research design is defined as

Design of a Clinical Case Series

• Living reference work entry
• First Online: 30 May 2024
• Cite this living reference work entry

• Nyaluma N. Wagala 5 ,
• Shaquille Charles 5 ,
• Soheil Sabzevari 5 , 6 &
• Albert Lin 5  

This chapter delves into the intricacies of designing and conducting clinical case series in orthopedic surgery, highlighting their significance in advancing medical knowledge and practice. It begins by elucidating the concept of evidence-based medicine and the importance of integrating clinical expertise with up-to-date research findings. Exploring the hierarchy of evidence in clinical research, the chapter emphasizes the valuable role of case series despite their lower level within this hierarchy. Addressing the process of initiating a case series, the chapter discusses key considerations such as defining the research question, identifying the study population, risk factors, and outcomes. Strengths and weaknesses of case series are analyzed, emphasizing their value in generating hypotheses and facilitating awareness about diseases or interventions. Practical guidance is provided on conducting statistical analyses, including strategies to mitigate biases and enhance validity. Drawing from examples in orthopedic surgery, this chapter illustrates how well-designed case series can influence clinical practice and pave the way for future research. Despite limitations, case series offer educational benefits and serve as a cornerstone for evidence-based medicine. Encouraging the production of high-quality case series, this chapter underscores their pivotal role in shaping the landscape of orthopedic surgery research and innovation.

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Department of Orthopaedic Surgery, UPMC Freddie Fu Sports Medicine Center, University of Pittsburgh, Pittsburgh, PA, USA

Nyaluma N. Wagala, Shaquille Charles, Soheil Sabzevari & Albert Lin

Department of Orthopaedic Surgery, Razavi Hospital, Imam Reza International University, Meshhad, Iran

Soheil Sabzevari

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Correspondence to Nyaluma N. Wagala .

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FIFA Medical Centre of Excellence, Clínica Espregueira, Porto, Portugal

João Espregueira-Mendes

Dept. Orthopaedics, Sahlgrenska University Hospital, Mölndal, Sweden

Jón Karlsson

UPMC Freddie Fu SportsMed Ctr, Orth Surg, University of Pittsburgh, Pittsburgh, PA, USA

Volker Musahl

McMaster University, Hamilton, ON, Canada

Olufemi R. Ayeni

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UPMC Freddie Fu Sports Medicine Center, Department of Orthopaedic Surgery, University of Pittsburgh, Pittsburgh, PA, USA

Volker Musahl MD

Division of Orthopaedic Surgery, McMaster University, Hamilton, ON, Canada

Mohit Bhandari

Mark R. Neaman Family Chair of Orthopaedic Surgery and Director, Orthopaedic & Spine Institute, NorthShore University HealthSystem, Skokie IL, Skokie, IL, USA

Jason L. Koh

Sports Clinic, Centre Hospitalier de Luxembourg – Clinique d’Eich, Luxembourg City, Luxembourg

Caroline Mouton

Luxembourg Institute of Research in Orthopaedics, Sports Medicine and Science (LIROMS), Luxembourg City, Luxembourg

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Wagala, N.N., Charles, S., Sabzevari, S., Lin, A. (2024). Design of a Clinical Case Series. In: Espregueira-Mendes, J., Karlsson, J., Musahl, V., Ayeni, O.R. (eds) Orthopaedic Sports Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-65430-6_118-1

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DOI : https://doi.org/10.1007/978-3-030-65430-6_118-1

Received : 01 December 2021

Accepted : 01 April 2024

Published : 30 May 2024

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Methodological quality of case series studies: an introduction to the JBI critical appraisal tool

Munn, Zachary 1 ; Barker, Timothy Hugh 1 ; Moola, Sandeep 1,2 ; Tufanaru, Catalin 1,3 ; Stern, Cindy 1 ; McArthur, Alexa 1 ; Stephenson, Matthew 1 ; Aromataris, Edoardo 1

1 JBI, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia

2 The George Institute for Global Health, Telangana, India

3 Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Sydney, NSW, Australia

Correspondence: Timothy Hugh Barker, [email protected]

The authors declare no conflict of interest.

Introduction: 

Systematic reviews provide a rigorous synthesis of the best available evidence regarding a certain question. Where high-quality evidence is lacking, systematic reviewers may choose to rely on case series studies to provide information in relation to their question. However, to date there has been limited guidance on how to incorporate case series studies within systematic reviews assessing the effectiveness of an intervention, particularly with reference to assessing the methodological quality or risk of bias of these studies.

Methods: 

An international working group was formed to review the methodological literature regarding case series as a form of evidence for inclusion in systematic reviews. The group then developed a critical appraisal tool based on the epidemiological literature relating to bias within these studies. This was then piloted, reviewed, and approved by JBI's international Scientific Committee.

Results: 

The JBI critical appraisal tool for case series studies includes 10 questions addressing the internal validity and risk of bias of case series designs, particularly confounding, selection, and information bias, in addition to the importance of clear reporting.

Conclusion: 

In certain situations, case series designs may represent the best available evidence to inform clinical practice. The JBI critical appraisal tool for case series offers systematic reviewers an approved method to assess the methodological quality of these studies.

Introduction

Systematic reviews aim to provide a comprehensive and rigorous synthesis of the best available evidence to inform health policy and practice. 1-4 Although case series are not traditionally included in systematic reviews assessing the effectiveness of an intervention or therapy, they have contributed greatly to the medical literature and can offer valuable information relating to the benefits and harms of certain treatments. 5,6 As such, case series can be considered for inclusion in systematic reviews of effectiveness, particularly in the absence of experimental designs such as randomized controlled trials and observational analytical studies.

There is an element of confusion regarding both the nomenclature and characteristics of a case series, with the definition varying across the medical literature, resulting in the inconsistent use of the term. 7-9 The gamut of case series is wide, with some studies claiming to be a case series that are realistically a collection of case reports, while others are more akin to cohort studies or even quasi-experimental, before and after studies. This has created difficulty in assigning case series a position in the hierarchy of evidence and identifying an appropriate critical appraisal tool. 7-9 This is not only a challenge with case series studies but also within the broader epidemiological literature, resulting in efforts to classify and group various features of different types of research studies through the use of algorithms or flowcharts. 10-13 In these guidance documents, case series are described as an observational and non-comparative study design.

According to one dictionary of epidemiology, case series are “a collection of subjects (usually, patients) with common characteristics used to describe some clinical, pathophysiological, or operational aspect of a disease, treatment, exposure, or diagnostic procedure.” 14 (p.33) It is noted that a case series “does not include a comparison group and is often based on prevalent cases and on a sample of convenience.” 14 (p.33) In the authors’ view, case series are best described as observational (that is, not experimental and not randomized), descriptive studies, without a control (or comparator group). Dekkers et al. 8 define a case series as a study in which “only patients with the outcome are sampled (either those who have an exposure or those who are selected without regard to exposure), which does not permit calculation of an absolute risk.” (p.39) The outcome could be a disease or disease-related. This is in contrast to cohort studies, where sampling is based on exposure (or characteristic), and case-control studies, where there is a comparison group without the disease.

All systematic reviews incorporate a process of critiquing and appraising the research evidence. The purpose of this appraisal is to assess the methodological quality of a study and to determine the extent to which a study has addressed the possibility of bias in its design, conduct, and analysis. 15 All studies selected for inclusion in a systematic review (that is, those that fulfill the a priori eligibility criteria described in the protocol) need to be subjected to rigorous assessment of their quality of conduct by two independent critical appraisers. The results of this appraisal can then be used to inform synthesis and interpretation of the results of the systematic review. 15

Systematic reviews often use critical appraisal tools that are study-design specific. There may be separate tools used to appraise randomized controlled trials, cohort studies, cross-sectional studies, and so on. 4 Because case series are an uncontrolled (and non-experimental) study design, they are associated with an increased risk of bias 5 and must be appraised with the same scrutiny expected of study designs associated with higher levels of evidence. 16 For example, the completeness of a case series contributes to its reliability, 8 with studies that indicate a consecutive and complete inclusion considered more reliable than those that do not.

The JBI approach to systematic reviews is one of pragmatism, where the aim is to include a summary of the best available evidence and not only randomized controlled trials. 17-19 As such, there was a need for a standardized tool that would allow for transparent and repeatable appraisals of case series included in systematic reviews of effectiveness. This paper documents the process of the creation and application of such a tool.

In 2014, a working group of researchers and methodologists was formed within JBI to investigate the use of case series studies in systematic reviews and the development of a critical appraisal tool for these designs. It was clear from the beginning that the group needed to ensure a clear understanding and definition for case series among all members. The group agreed with the principles outlined by Dekkers et al. 8 and defined case series as studies where only patients with a certain disease or disease-related outcome are sampled. Before proceeding to develop a new tool, the group conducted a search and review of existing methodological, epidemiological, and health research literature on case series as well as previously published appraisal tools for case series. Although few guides and tools were identified, 20-22 the group felt that this guidance inadequately covered all important methodological areas specific to case series designs. Over a period of one year with many methodological discussions, the group developed a tool, which was then piloted internally by the authors. Items covered in the tools were selected based on the authors’ review of the methodological literature and relevant items from other JBI tools. Based on the results of this pilot, the final tool was then drafted and sent to the JBI international Scientific Committee for further review and feedback. Following minor modifications, the tool was approved by the Scientific Committee and made available to JBI reviewers ( Table 1 ). 23 It was also embedded in the JBI System for the Unified Management, Assessment and Review of Information (JBI SUMARI; Adelaide, Australia, JBI). 24

Within the tool, some of the items relate to risk of bias, whereas others relate to ensuring adequate reporting and statistical analysis. A response of “no” to any of the following questions negatively impacts the overall quality of a case series.

How to use this tool

• Were there clear criteria for inclusion in the case series?
• The authors should provide clear inclusion criteria (and exclusion criteria where appropriate) for the study participants. The inclusion/exclusion criteria should be specified (eg, risk, stage of disease progression) with sufficient detail and all the necessary information critical to the study.
• Was the condition measured in a standard, reliable way for all participants included in the case series?
• The study should clearly describe the method of measurement of the condition. This should be done in a standard (ie, same way for all patients) and reliable (ie, repeatable and reproducible results) way.
• Were valid methods used for identification of the condition for all participants included in the case series?
• Many health problems are not easily diagnosed or defined, and some measures may not be capable of including or excluding appropriate levels or stages of the health problem. If the outcomes were assessed based on existing definitions or diagnostic criteria, then the answer to this question is likely to be “yes.” If the outcomes were assessed using observer-reported or self-reported scales, the risk of over- or under-reporting is increased, and objectivity is compromised. Importantly, researchers need to determine if the measurement tools used were validated instruments, as this has a significant impact on outcome assessment validity.
• Did the case series have consecutive inclusion of participants?
• Studies that indicate a consecutive inclusion are more reliable than those that do not. For example, a case series that states, “We included all patients (24) with osteosarcoma who presented to our clinic between March 2005 and June 2006” is more reliable than a study that simply states, “We report a case series of 24 people with osteosarcoma.”
• Did the case series have complete inclusion of participants?
• The completeness of a case series contributes to its reliability. 8 Studies that indicate a complete inclusion are more reliable than those that do not. As stated above, a case series that states, “We included all patients (24) with osteosarcoma who presented to our clinic between March 2005 and June 2006” is more reliable than a study that simply states, “We report a case series of 24 people with osteosarcoma.”
• Was there clear reporting of the demographics of the participants included in the study?
• The case series should clearly describe relevant participants’ demographics such as the following information where relevant: participant's age, sex, education, geographic region, ethnicity, and time period.
• Was there clear reporting of clinical information of the participants?
• There should be clear reporting of clinical information of the participants, such as the following information where relevant: disease status, comorbidities, stage of disease, previous interventions/treatment, results of diagnostic tests, etc.
• Were the outcomes or follow-up results of cases clearly reported?
• The results of any intervention or treatment should be clearly reported in the case series. A good case series should clearly describe the clinical condition post-intervention in terms of the presence or lack of symptoms. The outcomes of management/treatment when presented as images or figures can help in conveying the information to the reader/clinician. It is important that adverse events are clearly documented and described, particularly when a new or unique condition is being treated or when a new drug or treatment is used. In addition, unanticipated events, if any, that may yield new or useful information should be identified and clearly described.
• Was there clear reporting of the presenting sites’/clinics’ demographic information?
• Certain diseases or conditions vary in prevalence across different geographic regions and populations (eg, women men, sociodemographic variables between countries). The study sample should be described in sufficient detail so that other researchers can determine if it is comparable to the population of interest to them.
• Was statistical analysis appropriate?
• As with any consideration of statistical analysis, consideration should be given to whether there was a more appropriate alternate statistical method that could have been used. The methods section of studies should be detailed enough for reviewers to identify which analytical techniques were used and whether these were suitable.

This critical appraisal tool for case series studies has been publicly available on the JBI website since December, 2017. Since then, it has been used in systematic reviews 25-27 and cited in systematic review protocols. 28-30 As evidenced from these reviews and protocols, the inclusion of a case series is typically most beneficial in reviews of effectiveness, prevalence and/or incidence, and etiology and/or risk, particularly when there are no other studies to consider. 31

Recently, multiple new case series tools have been published in the literature. 5,22 Both Murad et al. 5 and Guo et al. 22 have documented the creation and provision of similar tools to evaluate the methodological quality of a case series. The majority of the questions included in both of these tools address similar issues to those presented in the JBI tool, with minor variations in wording that could have ramifications for how appraisers interpret the results after using each tool. While there are advantages and disadvantages associated with each tool, the assessment of risk of bias, particularly when assessing observational studies, may be too complex a task for any single tool. 32 Assessment of risk of bias can be further hampered by a lack of compatibility between the chosen tool and the review team, with some teams feeling more comfortable or familiar with one tool over another. This highlights the importance of piloting the tool during the critical appraisal process. Some questions may need to be tailored to suit the research focus, while a scoring framework of “yes,” “no,” or “not applicable (N/A)” may not be suitable for each question relevant to the study design or the research parameters. It is the authors’ opinion that all three tools provide a clear and logical format for the appraisal of case series. The advantage of the Guo et al. 22 and JBI tools is that they are designed specifically for case series (as opposed to a joint tool for case series and case reports), which allows them to have additional questions and be more specific to case series designs. 32

In addition to these tools, there is a tool that has been developed to assess the risk of bias when conducting an effectiveness review and when including non-randomized studies: the Risk of Bias in Non-randomised Studies of Interventions (ROBINS-I). 33 This is a domain-based tool, and although it is designed for non-randomized studies, it is particularly designed for studies with “cohort-like” designs or designs with a control group. As case series studies do not have a control group, this tool may not be ideal for these study designs, nor would the Newcastle-Ottawa scale. 34 In a review of tools for critically appraising non-randomized studies, Quigley et al. 35 recommend that because there is no current consensus on which tool to use, systematic reviewers should select an appropriate tool based on the study design of selected papers for inclusion in their review.

Many researchers prefer using a domain-based approach in the critical appraisal of primary literature. 36,37 The main domains of bias assessed in observational studies include confounding bias, selection bias and information bias (including measurement, detection, classification, analysis, and reporting bias), and these biases can be assessed through the use of signaling questions. 37 Although the tool presented in this paper has not been designed based on the domain approach, the questions can be seen as signaling questions for particular domains of bias. For example, questions 1, 4, and 5 can be considered signaling questions for the domain “bias in selection of participants into the study”; questions 2 and 3 for the domain “bias in measurement of outcomes”; questions 6 and 7 for the domain “bias in selection of the reported results”; and question 8 for the domain “bias due to missing data.”

The authors often receive queries from reviewers wishing to use the tool to provide advice on how much weight to assign each question, and what the cut-off score should be for inclusion in a systematic review. These questions presuppose that the purpose of appraisal in systematic reviews is to include only those studies that are of high quality and to exclude those of poor quality. While this is one way to use the results of critical appraisal in reviews, it is not the only approach, and it may not be appropriate in many situations. The guidance to authors wishing to use this tool in terms of cut-off values/scores and determining whether a study is low, moderate or high quality, is that these thresholds are best decided by the systematic reviewers themselves. Generally, cut-off scores are advised against, because the critical appraisal questions are not all “equal.” As such, simply tallying the “yes” responses does not truly give an accurate indication of the specific problems of a study. The authors suggest presenting the results of critical appraisal for all questions via a table rather than summarizing with a score. Ideally, two reviewers will be involved in the critical appraisal for the review.

This tool is now in active use by the JBI Collaboration and other systematic reviewers who are including case series designs in their reviews. This tool was developed based on methodological and epidemiological principles and has been reviewed internally by the author group in addition to the JBI Scientific Committee. It has been deemed as acceptable and appropriate by these groups and as such has demonstrated face validity. Further validation efforts are now required to establish the psychometric properties of the tool in addition to other issues, such as its acceptability, timeliness, and ease of use. As previously described, another program of work relates to transferring this tool into a domain-based approach. However, given the lack of any current validated tool for critiquing case series studies, it was the view of the group that this tool be made widely available to assist systematic reviewers with the conduct of their reviews.

When there is limited availability of high-quality experimental studies (such as randomized controlled trials) on the effectiveness or harms of an intervention, case series may represent the best available evidence to inform clinical practice. As such, a critical appraisal tool is required. The JBI critical appraisal tool for case series offers systematic reviewers an approved method to assess the methodological quality of these studies.

Acknowledgments

Dr. Kylie Porritt for her contribution during the drafting of this paper.

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Quantitative study designs: Case Studies/ Case Report/ Case Series

Quantitative study designs.

• Introduction
• Cohort Studies
• Randomised Controlled Trial
• Case Control
• Cross-Sectional Studies
• Study Designs Home

Case Study / Case Report / Case Series

Some famous examples of case studies are John Martin Marlow’s case study on Phineas Gage (the man who had a railway spike through his head) and Sigmund Freud’s case studies, Little Hans and The Rat Man. Case studies are widely used in psychology to provide insight into unusual conditions.

A case study, also known as a case report, is an in depth or intensive study of a single individual or specific group, while a case series is a grouping of similar case studies / case reports together.

A case study / case report can be used in the following instances:

• where there is atypical or abnormal behaviour or development
• an unexplained outcome to treatment
• an emerging disease or condition

The stages of a Case Study / Case Report / Case Series

Which clinical questions does Case Study / Case Report / Case Series best answer?

Emerging conditions, adverse reactions to treatments, atypical / abnormal behaviour, new programs or methods of treatment – all of these can be answered with case studies /case reports / case series. They are generally descriptive studies based on qualitative data e.g. observations, interviews, questionnaires, diaries, personal notes or clinical notes.

What are the advantages and disadvantages to consider when using Case Studies/ Case Reports and Case Series ?

What are the pitfalls to look for?

One pitfall that has occurred in some case studies is where two common conditions/treatments have been linked together with no comprehensive data backing up the conclusion. A hypothetical example could be where high rates of the common cold were associated with suicide when the cohort also suffered from depression.

Critical appraisal tools 

To assist with critically appraising Case studies / Case reports / Case series there are some tools / checklists you can use.

JBI Critical Appraisal Checklist for Case Series

JBI Critical Appraisal Checklist for Case Reports

Real World Examples

Some Psychology case study / case report / case series examples

Capp, G. (2015). Our community, our schools : A case study of program design for school-based mental health services. Children & Schools, 37(4), 241–248. A pilot program to improve school based mental health services was instigated in one elementary school and one middle / high school. The case study followed the program from development through to implementation, documenting each step of the process.

Cowdrey, F. A. & Walz, L. (2015). Exposure therapy for fear of spiders in an adult with learning disabilities: A case report. British Journal of Learning Disabilities, 43(1), 75–82. One person was studied who had completed a pre- intervention and post- intervention questionnaire. From the results of this data the exposure therapy intervention was found to be effective in reducing the phobia. This case report highlighted a therapy that could be used to assist people with learning disabilities who also suffered from phobias.

Li, H. X., He, L., Zhang, C. C., Eisinger, R., Pan, Y. X., Wang, T., . . . Li, D. Y. (2019). Deep brain stimulation in post‐traumatic dystonia: A case series study. CNS Neuroscience & Therapeutics. 1-8. Five patients were included in the case series, all with the same condition. They all received deep brain stimulation but not in the same area of the brain. Baseline and last follow up visit were assessed with the same rating scale.

References and Further Reading  

Greenhalgh, T. (2014). How to read a paper: the basics of evidence-based medicine. (5th ed.). New York: Wiley.

Heale, R. & Twycross, A. (2018). What is a case study? Evidence Based Nursing, 21(1), 7-8.

Himmelfarb Health Sciences Library. (2019). Study design 101: case report. Retrieved from https://himmelfarb.gwu.edu/tutorials/studydesign101/casereports.cfm

Hoffmann T., Bennett S., Mar C. D. (2017). Evidence-based practice across the health professions. Chatswood, NSW: Elsevier.

Robinson, O. C., & McAdams, D. P. (2015). Four functional roles for case studies in emerging adulthood research. Emerging Adulthood, 3(6), 413-420.

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What is Case Series?

• Asploro Journal of Biomedical and Clinical Case Reports
• ISSN : 2582-0370
• Article Type : Editorial
• Asp Biomed Clin Case Rep. 2018 Aug 17;1(1):10-15

El-Gilany AH 1* 1 Professor of Public Health, Faculty of Medicine,  Mansoura University , Egypt

Corresponding Author:  Abdel-Hady El-Gilany MD  ORCID ID Address:  Professor of Public Health & Preventive Medicine, Faculty of Medicine,  Mansoura University  Egypt. Received date : 06 August 2018;  Accepted date : 16 August 2018;  Published date : 17 August 2018

Citation:  El-Gilany AH. What is case series?. Asp Biomed Clin Case Rep. 2018 Aug 17;1(1):10-15.

Copyright  © 2018 El-Gilany AH. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords:  Case Series, Exposure Series, Definition, Types, Importance, Limitations

This is the second part of a series on case reports and case series studies. It will help junior researchers to comprehend what is the case series/exposure series as a type of research. It highlights the definition, types, importance, limitations, and differences between case series and exposure series. Examples of important historical case series that were instrumental in the early identification of health problems will be mentioned. A special editorial will be devoted to consecutive controlled case series (CCCS)/ self-controlled case series (SCCS) as an important research method.

Introduction

Case series (also known as clinical series) represents one of the most basic types of study designs, in which researchers describe the experience of a small group of people. It presents a detailed account of the clinical experience of individual study subjects and can evaluate large numbers of individuals and summarize the data using descriptive statistical measures [1]. A case series is a variation of a single case report in which the author describes several cases and their relation to one another and to the existing body of literature.

The Dictionary of Epidemiology defined a case series as – a collection of patients with common characteristics used to describe some clinical, pathophysiological or operational aspects of a disease, treatment or diagnostic procedures [2]. Case series is an observational, descriptive research design. It is most useful for describing the potential effectiveness of new interventions, for describing the effectiveness of interventions on unusual diagnoses, and for describing unusual responses (either good or bad) to interventions. Case series can be conducted retrospectively or prospectively. The primary distinction between case reports/series and the single-subject experiment is that the researcher does not manipulate the intervention in a case report/series but merely describes/documents what happened during the normal course of the intervention. Despite limitations, case series can often have a significant impact on the current practice of medicine and they are often used to put together case definitions of new diseases and to define future areas of clinical study [3]. However, no causal inferences should be made from case series regarding the efficacy of the investigated treatment [4]. A case series samples patients with both a specific outcome and a specific exposure, or samples patients with a specific outcome and includes patients regardless of whether they have specific exposures [5].

Types of Case Series

There are many classifications for case series.

Informal vs. Formal Case Series : [6,7]

• Informal case series : Cases are selected for specific reasons: best case, worse case, significant variations. The format of this kind of case series is: introduction; case 1, case 2, case 3, etc. (each case is presented as a short case description); discussion (cases will be compared to one another, related cases to the current literature, implications of the findings, teaching points and what changes in clinical practice this might engender).
• Formal case series : Include all cases of a specific type, or with specific selection criteria, presented more like a cohort study than a single case report and its format is introduction methods, results, and discussion/conclusions.

Consecutive vs. Non-Consecutive Case Series : [5,8]

• Consecutive case series : Includes all eligible patients identified by the researchers during the study period. The patients are treated in the order in which they are identified. Consecutiveness increases the quality of the case series.
• Non-consecutive case series : Includes some, but not all, of the eligible patients identified by the researchers during the study period.

Exposure or Outcome-Based Sampling : [5,9]

• Exposure-based sampling : Include all patients treated and have specific outcomes or adverse events. Sampling is based on both a specific outcome and presence of a specific exposure.
• Outcome-based  sampling: Includes patients with the specific outcome regardless of exposure. Thus neither absolute risk nor relative risk can be calculated. Selection is based only on a specific outcome, and data are collected on previous exposures.

Clinical vs. Population-Based Series : [10-12]

• Clinical case series : Usually a coherent and consecutive set of cases of a disease recruited from one or more center by one or more researcher. It is a clinic-based register of cases that are analyzed together to learn about the disease. They are of value in epidemiology for studying symptoms and signs, creating case definitions as well as clinical education, audit, and research.
• Population-based case series : When a clinical case-series is limited and complete for a defined geographical area for which the population is known, it is a population-based case-series consisting of a population register of cases. It is usually compiled for administrative and legal reasons.

By knowing the past history of these patients, including examination of past medical records, and by continuing to observe them to death, health professionals can build up a picture of the natural history of a disease in clinical case series. Population case-series is a systematic extension of this series but which includes additional cases, e.g. those dying without being seen by the clinicians. It adds breadth to the understanding of the spectrum and natural history of the disease. Information on the population permits calculation of rates, understanding the distribution of disease in populations and to the study of variations over time, between places and by population characteristics. Epidemiologically the most important case-series are registers of serious diseases or deaths, and of health service utilization, e.g. hospital admissions.

Design of Case Series

Case series research is a descriptive study to present patients in their natural clinical setting. The case series can be retrospective or prospective and may be consecutive or nonconsecutive depending on whether all cases presenting to the reporting authors over a period were included, or only a selection [13].

The study question should be focused and appropriate. The question should not be whether the investigated treatment is more effective or safer than another treatment. It should list the study population, the intervention and the primary outcome [4].

The setting : Select a suitable observation period and identify cases with events in this period. It may be tempting to include patients seen over a large period of time to increase sample size. However, the use of a short inclusion period minimizes known and unknown changes over time in co-interventions, prognosis, and even in the intervention under study [4,14].

Number of cases : there is no thumb rule or a magic number. The general number of cases reported in a case series range from 20 to 50, but may vary from as few as 2 or 3 to as many as more than 100 [10] or even thousands [6].

N.B. Case-only analyses are sometimes performed in genetic epidemiology to investigate the association between an exposure and a genotype [15].

What to look for : Look at when the events arose in relation to the exposures. Reports of case series usually contain detailed information about the individual patients. This includes demographic information (for example, age, gender, ethnic origin) and information on diagnosis, treatment, response to treatment, and follow-up after treatment [4,16,17].

• What : The diagnosis or case definition should be clear and applied equally to all individuals in the series. The case definition should mention the inclusion and exclusion criteria, which should be based on widely used validated definitions. If authors use their own criteria, definition and justification are necessary to enable readers to compare the studied population with their own patients.
• When : The date when the disease or death occurred (time).
• Where : The place where the person lived, worked etc (place).
• Who : The characteristics of the population (person). Noting the socio-demographic characteristics of a series of cases, as well as the temporal and spatial distributions can sometimes provide a clue to risk factors and hence help generate a hypothesis. This can be tested subsequently with more elaborate analytic studies.
• The opportunity to collect additional data from medical records (possibly by electronic Data linkage) or the person directly.

A detailed description of the intervention and the co-intervention should be stated. This will ensure repeatability of the study by other investigators. It is very important to thoroughly describe co-interventions. Additionally, indications for the studied treatment should be explained. This will primarily determine the consistency of the patient group [4].

The blinding of outcome assessors is ideal in every kind of research design and can be implemented quite usefully in case-series studies (e.g., by having some investigators collect data only on an outcome and others collect data only on patient characteristics). This prevents the investigators’ measurements from being influenced (intentionally or unintentionally) by their personal treatment preference [4].

The method of data acquisition (telephone interview, clinical measurement, or chart review) should be addressed in the study report for the sake of repeatability and the appraisal of measurement bias [4].

Analysis : As the design of a case series is descriptive, only descriptive statistics should be used. Case-series data are analyzed using rates. In three circumstances (spatial clustering, stable population and when there is no suitable denominator) use proportional ratios, not rates.

Findings can be presented as proportions (%) of the study populations with the outcome, confidence intervals; means, standard deviations for continuous variables and consider subgroups that need data presented separately [18]. No comparative tests yielding p values should be done. By describing summary statistics, the author errs on the conservative side of speculation and avoids misleading with fancy probability statistics [19].

Reporting:  A statement of the external validity of the obtained data should be given. This includes (1) patient characteristics and (2) completeness of follow-up. The presence of chance and the presence, direction, and magnitude of bias should be acknowledged [4].

Patients may differ according to prognostic variables, such as age, etiology, and disease severity among geographical regions. This may complicate comparisons with other reports or explain discrepancies.

The follow-up rates and reasons for loss to follow-up should be stated. Completeness of follow-up varies considerably among similar case series, making it difficult for readers to compare them. Therefore, authors should be cautious when interpreting their own results in relation to results of apparently similar case series [20].

No absolute conclusions on the studied treatment should be stated, the lack of a comparison group prohibits any hypothesis from being tested. Valid conclusions basically repeat the descriptive study findings e.g. our patients treated by treatment X showed good outcome Y after Z months of follow-up [21].

Advantages [4,14,22-26]

• High external validity: the study results are closer to those obtained in routine clinical practice and may, therefore, be considered more relevant.
• It could be useful when a randomized controlled trial is not appropriate or possible.
• No interference in the treatment decision process
• A wide range of patients
• Study conduct takes little time
• Easy to write and can be useful in new observations or disease.
• Useful for hypothesis generation, but conclusions about etiology cannot be made.
• Informative for very rare disease with few established risk factors.
• Informs patients and physicians about natural history and prognostic factors.
• Easy and inexpensive to do in hospital settings.
• Can help identify potential health problems such as the acute outbreaks of the severe acute respiratory syndrome (SARS).
• Stimulate interest in an area, leading to more detailed studies, and advancing knowledge.
• An important link between clinical medicine and epidemiology
• One of the first steps in the outbreak investigation
• Can provide the key to sound case-control and cohort studies and trials. Many case series are followed by clinical trials.
• Provides ―anecdotal‖ evidence about a treatment or adverse reaction.
• The case series method is self-matched: estimation is within-individuals.
• As a result, all fixed confounders are automatically controlled: for example,  socioeconomic level, genetic factors, location, diet, state of health.
• Only uses information on cases: no controls are required.
• Studying predictive symptoms, signs, and tests.
• Creating case definitions
• Clinical education, audit, and research
• Health services research
• Establishing safety profiles

Disadvantages [ 1,4,10,16,20,22,26-28 ]

• Lack of a control (or comparison) group this raises the question ―compared to what?
• Data collection often incomplete.
• Generally short-term
• Lack of a denominator to calculate rates of disease.
• Strong publication bias favoring positive results.
• Cannot study cause and effect relationships.
• Cannot assess disease frequency
• Lacks external validity because cases may not be representative.
• An outcome may be a chance finding, not characteristic of the disease.
• Cannot easily examine disease etiology
• Not planned before and lacks hypothesis and are often not considered by many authorities to be research studies.
• Selection bias (investigators self-select): The selective nature and the limited amount of information provide little evidence of causality and cannot say much about patterns of disease occurs due to the seasonal nature of some diseases. A series of patients with a certain illness and/or a suspected linked exposure draw their patients from a particular population (such as a hospital or clinic) which may not appropriately represent the wider population.
• Very low internal validity due to the lack of a comparator group exposed to the same array of intervening variables. The effects seen may be wholly or partly due to intervening effects such as the placebo effect, Hawthorne effect, time effects, practice effects or the natural history effect.
• Information bias:  Cases can be retrieved retrospectively or collected prospectively. Information on cases retrieved retrospectively is generally more objective, as it is collected routinely in relevant medical records. Missing or incomplete information could be an issue. For prospectively collected information, it is desirable to have standard protocols and forms to collect the necessary information, to avoid missing data for some patients. In a purely descriptive case series, confounding is not a concern, as the association between a certain factor and an outcome is not being studied.
• Sampling variation : A precise estimate of the rate of a disease, independent from chance, can be obtained only by increasing the number of diseased subjects.

Case Series that was Instrumental in the Early Identification of Health Problems

– Congenital Rubella Syndrome : The classic description of a series of infants born with congenital cataracts, some with additional cardiac abnormalities, in Australia in 1941. This led Gregg in Sydney to postulate a causal link between a severe epidemic of rubella that had occurred six to nine months before the children were born and the subsequent abnormalities. It is now well known that if a woman develops rubella during pregnancy it may affect her unborn baby.

– A case report published in the UK in 1961 described the development of a pulmonary embolism in a 40-year-old pre-menopausal woman, five weeks after she had started using an oral contraceptive (OC) to treat endometriosis. Because pulmonary embolism is rare in women of that age, the author suggested that it might have been caused by the OC, particularly since it was a novel exposure at that time. More detailed studies have consistently shown that there is an association between the use of OCs and the risk of pulmonary embolism.

– A report of a series of five cases of Pneumocystis carinii pneumonia that occurred in young, previously healthy, homosexual men in three Los Angeles hospitals in a six-month period during 1980–81. Until then, this disease had been seen almost exclusively in immunosuppressed e.g. the elderly, the severely malnourished and those on anti-cancer chemotherapy. This cluster of cases in young men suggested that the men were suffering from a previously unknown disease, possibly related to sexual behavior which was proved to be HIV/AIDS.

[1].  Kestenbaum B, “An introduction to clinical research”.  Epidemiology and biostatistics : 25, 2009.

[2].  Porta M (ed). A dictionary of epidemiology /edited for the International Epidemiological Association, 5th edition.  Oxford University Press , UK: pp: 33, 2008 .

[3].  Suresh K, Suresh G, Thomas SV, “Design and data analysis 1 study design”.  Ann Indian Acad Neurol , vol.15, no.2: 76–80, 2012 .

[4].  Kooistra B, Dijkman B, Einhorn TA, et al., “How to design a good case series”.  J Bone Joint Surg Am , vol.91, (Suppl 3): 21 -26, 2009.

[5].  Dekkers OM, Egger M, Altman DG, et al., “Distinguishing case series from cohort studies”.  Ann Intern Med,  vol.156, (1 Pt 1): 37-40, 2012.

[6].  Carey TS, Boden SD, “A Critical Guide to Case Series Reports”.  Spine , vol.28, no.15: 1631–34, 2003 .

[7]. Lutheran HealthCare, “Guidelines for Writing Case Reports & Case Series”. Accessed: August 1, 2018

[8].  National Cancer Institute Dictionary of Cancer Terms. Accessed: August 12, 2018

[9].  Crandall M, Eastman A, Violano P, et al., “Prevention of firearm-related injuries with restrictive licensing and concealed carry laws: an eastern Association for the Surgery of trauma systematic review”.  J Trauma Acute Care Surg,  vol.81, no.5: 952–60, 2016.

[10].  Omair A, “Selecting the appropriate study design for your research: Descriptive study designs”.  J Health Spec , vol.3, no.3: 153-56, 2015.

[11].  Mandil A, “Study Designs in Epidemiology. Lecture presented at High Institute of Public Health University of Alexandria”.  Accessed: August 6, 2018

[12].  Study design Bhopal R, Bruce and Usher J Professor of Public Health, Public Health Sciences Section, Division of Community Health Sciences, University of Edinburgh, Edinburgh EH89AG. Accessed: August 6, 2018

[13].  Esene IN, Ngu J, El Zoghby M, et al., “Case series and descriptive cohort studies in neurosurgery: the confusion and solution”.  Childs Nerv Syst,  vol.30, no.8: 1321–32, 2014 .

[14].  Whitaker H. Case series studies:  rationale, design and analysis. Open University, UK. Accessed: August 11, 2018

[15].  Khoury MJ, Flanders WD, “Nontraditional epidemiologic approaches in the analysis of gene-environment interaction: case-control studies with no controls”. Am J Epidemiol, vol.144, no.3: 207–13, 1996.

[16].  Yu I, Tse S, “Workshop 3 — Sources of bias in case series, patient cohorts, and randomized controlled trials”.  Hong Kong Med J,  vol.17, no.6: 478-79, 2011.

[17].  Howick J. Introduction to study design. Accessed August 13, 2018

[18].  Ford DE, introduction to clinical research, study design, case series and cross-sectional.  July 14, 2010. Accessed: August 13, 2018

[19].  Griffin D, Audige L, “Common statistical methods in orthopaedic clinical studies”.  Clin Orthop Relat Res,  vol.413: 70-79, 2003 .

[20].  Dalziel K, Round A, Stein K, et al., “Do the findings of case series studies vary significantly according to methodological characteristics?”,  Health Technol Assess,  vol.9, no.2: iii-iv, 1-146, 2005.

[21].  von Elm E, Altman DG, Egger M, et al., “The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies”.  Lancet , vol.370, no. 9596: 1453-57, 2007 .

[22].  Cummings P, Weiss NS, “Case series and exposure series: the role of studies without controls in providing information about the etiology of injury or disease”.  Inj Prev , vol.4, no.1: 54–57, 1998 .

[23].  Hartz A, Marsh JL, “Methodologic issues in observational studies”.  Clin Orthop Relat Res , vol.413: 33-42, 2003.

[24].   Audigé L, Hanson B, Kopjar B, “Issues in the planning and conduct of nonrandomized studies”.  Injury,  vol.37, no.4: 340-48, 2006.

[25].  Degu G, Yigzaw T, “Lecture notes. For health science students. Research methodology”.  Ethiopia Public Health Training Initiative:  P.25, 2006.

[26]. Webb P, Bain C, “Essential epidemiology. An introduction for students and health professionals. Second Edition”: P.72, 2011.

[27].  Cole P, “Introduction. In: Breslow NE, Day NE, editors. Statistical Methods in Cancer Research: The Analysis of Case-control Studies. IARC Publication No. 32. Vol. 1. Lyon: International Agency for Research on Cancer; 1980”. Accessed: August 13, 2018

[28].  Polgar S, Thomas SA, “Introduction to research in the health Sciences”.  Churchill Livingstone . 2013

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• v.12(4); 2012 Dec

Clinical “case series”: a concept analysis

To analyze the concept of “case series” in the medical literature compared with case reports.

A PubMed search for articles published during 2009 which had “case series” in their title was performed. A total number of 621 articles were retrieved. 586 papers were included in the analysis and 35 were excluded (18 were commentary letters, 5 were not in English, and twelve could not be retrieved by our Library). The number of patients and category of these articles were analyzed.

The median (range) of the number of cases of articles having “case series” in their title was 7 (1–6432) cases. 186/ 586 articles had less than 5 cases (31.7%, 95% CI (28.3–35.1%)). The median (range) of the number of cases of articles having “case report” as their publication type was 4 (1–178) cases. Out of the 219 articles categorized as case reports 114 (52.1%, 95% CI (45.6–58.6%)) had less than five cases.

Conclusions

The concept of “case series” is not well defined in the literature and does not reflect a specific research design. We suggest that a case series should have more than four patients while four paitents or less should be reported individually as case reports.

Introduction

There has been a recent trend in some journals to stop publishing case reports and publish more original articles instead. 1 , 2 This is possibly driven by the desire to get a higher impact factor, to properly utilize the limited space in the journals with economical gains, and to effectively use the time of the reviewers. This approach may have a negative impact on understanding the pathophysiology and management of rare diseases. Furthermore, group outcomes may not reflect exactly what happens in individual patients. 3 , 4 Reporting a study with a small number of patients may turn out to be very useful especially during an epidemic. Historically, reporting case series with small number of patients raised important concerns regarding serious conditions like the relationship between liver adenomas and contraceptive pills, Kaposi's sarcoma and AIDS, and the toxic effects of high concentrations of oxygen on the optic nerve in newborn infants. 5

Some journals have gone around that by accepting case series instead of case reports or alternatively establish a sister journal for case reports so as not to lose this important advantage. 1 An endeavor to launch indexed journals publishing only case reports was also attempted. 6 We have repeatedly noticed, during submitting articles to refereed journals, that the difference between a case series and a case report is not well defined. Both are seperate types of observational studies. 5 , 7 A case report is the smallest publishable unit in the medical literature while a case-series is an aggregation of several similar cases. 5 There is no defined limit for the smallest number of a case series. Some authors accepted even three cases to be a case series. 8 Furthermore, the style of reporting each of these types is different.

We were personally lost between the instruction of authors and the personal opinion of editors on defining a case series. Case series were some times rejected on the basis that they were considered by editors as case reports (personal expereince). We could not find a clear distinction between these two types in the medical literature and we aimed in this study to analyze the concept of “case series” as used recently in the medical literature and whether it is different from case reports.

A PubMed search was made through PubMed website 9 using the term “case series” between brackets. Search was limited to the title filed and the publication date between 1st of January 2009 to 31st of December 2009. The site was accessed on 18th of October 2010. Publications type was accessed on individual abstracts and tabbed. Some articles had more than one type which was vertically organized. The first line was considered as the first type, the second line as the second type, and the third line as the third type.

A total number of 621 articles were displayed. The abstracts of these articles were printed and reviewed manually. The number of cases in each paper was searched manually on the hard copy. 18 papers (letters to the Editor as commentaries on other published articles) and five non-English articles were excluded. 31 abstracts didn't have enough data regarding the number of studied cases. 19 full articles were retrieved through The National Medical Library of the Faculty of Medicine and Health Sciences, UAE University while the other 12 articles could not be retrieved and were excluded from the study. A total number of 586 papers were included in the analysis.

The “publications type” was searched directly from the website as described above. This was available only on 352 out of 586 articles (60.1%).

An excel program was made to enter the “number of cases” and “the publication types” for each article. Data were analyzed with the PASW Statistics 18, SPSS Inc, USA. A standard formula to calculate the 95% confidence interval (95% CI) of proportions was used which is: 95% CI = p ± 1.96 x square root of (pq/n), where p is the studied portion and q is the alternate portion and n is the sample size. 10

The mean (SD) of the number of cases of articles having “case series” in their title was 57.2 (357.6) cases while the median range of the number of cases was 7 (1–6432) cases. Majority of these articles had 10 cases or less (63%) ( figure 1 ). 186 out of the studied 586 articles had less than 5 cases (31.7%, 95% CI (28.3–35.1%)). One paper had a single case reported as case series in a prestigious journal. 11 The largest number of patients was 6432 patients. 12 PubMed categories were available in 352 articles. 219 articles (62.2%, 95% CI (57.4–67%) were categorized as case report ( table 1 ). The mean (SD) of the number of cases of articles having “case report” as their publication type was 8.2 (15.4) cases while the median range of the number of cases was 4 (1–178) cases. 85% of those categorized as case reports had 10 patients or less ( figure 2 ). Out of the 219 articles categorized as case reports 114 (52.1%, 95% CI (45.6–58.6%)). had less than five cases compared with 105 (47.9%, 95% CI (41.4–54.4%)) having 5 or more cases. Only one study (0.5%) categorized as case report had one case. Other categories are shown in table 1 . This covered a wide range of research designs including randomized controlled trials in three articles and meta-analysis in one article.

Publication type, as defined by the U.S. National Library of Medicine, National Institutes of Health, of articles having “case series” in their title, published during 2009 and indexed by the PubMed website

Number of subjects studied in papers published during 2009 by the U.S. National Library of Medicine, National Institutes of Health “ PubMed” that have “case series” in their title. Total number of publications = 586 papers

Number of subjects of papers published during 2009 by the U.S. National Library of Medicine, National Institutes of Health “PubMed” that have “case series” in their title and categorized as “case report”. Total number of publications = 219 papers

An accurate observation may turn out to be the first step towards an important discovery in science. Similarly, many diseases were first observed at the bedside. A good descriptive study has a clear, specific, and measurrable definition of the studied disease. 5 Although it is possible to carry out large-scale randomized trials for rare conditions when resources are available, this may turn out to be extremely difficult and expensive. Furthermore, the design of observational studies and randomized trials answer different questions.

Both case reports and case series lack comparison groups, their data may be biased and incomplete. Despite that, they are useful for generating hypotheses for future studies. 13

Definitions

According to the latest version of the Dictionary of Epidemiology, a case series is defined as “a collection of patients with common characteristics used to describe some clinical, pathophysiological or operational aspects of a disease, treatment or diagnostic procedures”. 14 A case report is a “detailed description of a few patients or clinical cases with an unsual disease or complication, uncommon combinations of diseases, and unusual or misleading semiology, cause or outcome”. 14 Interestingly, The fourth version of the same dictionary which was published in 2001 did not have a defnition for a case series neither a case report indicating that epidemiologists have only recently tried to define these terms. 15 Even a standard Evidenced-based Medicine book did not differentiate between a case series and a case report. 16 The Centre for Evidence-Based Medicine, University of Oxford, UK has defined case-series as “a report on a series of patients with an outcome of interest” 17 .

Other definitions indicate that a case series has few patients. The Medical Research Council of South Africa defined it as “an uncontrolled observational study involving an intervention and outcome for more than one person ” 18 . The Centre for training and Research in Public Health, Italy defined case-series as a “report of a number of cases of disease” 19 . The National Cancer Institute of USA defined case series as “a group or series of case reports involving patients who were given similar treatment” 20 . Interestingly, the Mesh database site of PubMed does not have a definition for case series neither it was considered as a catgory when classifying the papers having “case series” in their title 21 . Some investigators do not include “case series” in the list of types of studies because they are generally not planned and do not involve a research hypothesis 22 .

It is very clear from these definitions that there is no clear distinction between a case report and a case series in the literature. The results of our paper reflect this finding. Some papers, even in prestigious journals, considered one case as a case series 11 and another labeled a group of more than 6000 cases as a case series 12 . We think that this misconception stemmed from clinicians who used the “case series” term linguistically as a series of patients collected over a period of time without considerations to the research design. This misconception was also carried out to the definition of a case report. Interestingly, the Mesh database site of PubMed 21 defined case reports as “Clinical presentations that may be followed by evaluative studies that eventually lead to a diagnosis” which is very similar to the definition of a case series. The National Cancer Institute of USA defined a case report as “a detailed report of the diagnosis, treatment, and follow-up of an individual patient containing some demographic information about the patient” 20 .

Statistical and study design considerations

The variance of the data, the difference between the means, and the power of a study will decide the sample size needed for a study. Finding a difference between two groups depends on the standard error of the mean of each of these groups.

It is obvious that if data of a group of subjects are to be summarized statistically, then a minimum number of subjects is needed to be valid. We have found from experience that, five is the minimum reasonable number of independent subjects in a group so as to combine their data 23 – 25 That is because, the standard error of the mean, which is used for comparisons, will be much larger for a number of subjects less than that. The standard error of the mean equals the standard deviation (a marker of variation in the data) divided by the square root of the sample size. 10 This opinion agrees with Patterson et al who suggested that five cases is the lowest advised number of a case series. 7

Nevertheless, it is important to stress that the number of patients per se will not indicate the required research design. Clincial trials were performed even in a single patient using himself/herself as his/her own control. 26 Using this approcah, randomized controlled trials in a specific patients (N=1 clinical trial) were used to define the best treatment for that patient. 26

The style of a case report and a case series

A useful definition of a case report that we have found in the literature was “a description of clincial events of one or several patients in a narrative form”. 27 This, by surface validity, is similar to the patient's medical report. Each patient will have his/her own medical report which is written in a seperate section. Case series will contain individual patients' data like demography, diagnosis, and management. Data of a small case series can be presented as a table and pooled together if needed without the need for individual detailed desription 28 . This may occasionally alert clinicians to unnoticed serious clincial events. 28 , 29 This approach also enabled auhtors to develop unique new management algorithms for treating rare serious conditions 30 , 31 . Furhtermore, a case series may have been collected over a specific period of time which should be mentioned in the paper. A case series can be consecutive if all eligible patients were identified by the researchers during the study period. Alternatively, it can be nonconsecutive if it includes some, but not all, of the eligible patients. 32 , 33

We think that the distinction between a case report and a case series should be clear in the instruction of authors of different journals. This will save the time of the authors and editors and enhance the review process of medical journals. Some journals will accept only a case series design but not a case report. We suggest that patients less than 5 to be reported individually as case reports and those above 4 to be presented as a case series. Our study has shown that more than 30% of the papers having “case series” in their title have less than 5 cases and more than 50% of those “case series” labeled as a case report have less than 5 cases. The upper limit of a case series could not be defined by us but we suggest ten as an upper limit, similar to what was suggested by the European Urology 34 . This journal has clear instructions to authors that a “case series” should report on no more than 10 patients. An observational study of more patients based on rates is a different category and should be possibly labeled as a rate-based descriptive study. 7

In summary we have shown that the concept of “case series” is not well defined in the recent literature. We tried to analyze this concept and came with a suggestion that a case series should have more than four patients while four paitents or less should be reported individually as case reports. We hope that our suggestion will be accepted by the scientific community.

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Chapter 7:  Case Reports and Case Series

Jane R. Mort; Olayinka O. Shiyanbola

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Chapter objectives, key terminology, introduction, case reports.

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Discuss the objectives of case series and case reports

Outline the necessary components of case reports

Describe design and methodology of case series studies

Evaluate strengths and weaknesses of case reports and case series

Evaluate the results reported in case reports and case series

Case report

Case series

Publication bias

Reliability

Case reports and case series are descriptive studies that recount a patient scenario complete with pertinent medical information such as laboratory values, medications, and diagnoses. 1 , 2 A case report includes a detailed discussion of a unique medical scenario of a single case or event in light of the currently available literature and provides an evaluation of the findings. 3 Case series describe “a group of patients with similar diagnoses or undergoing the same procedure followed over time.” 4 Although case reports and case series are at the lower end in the hierarchy of evidence, they provide valuable information to practitioners and policy makers. 1 In fact, five of the “51 Landmark Articles in Medicine” identified over a 150-year period were case reports. 5–7

With increasing emphasis on randomized studies for evidence-based medicine, some have come to question the need and utility of case reports and case series. 8 , 9 Over the last several years, the number of published case reports has declined due to the perception that they are anecdotal and limited in their ability to be generalized. 5 In addition, publication costs, limitations in print space, need for peer reviewers, journal competition, and emphasis on the impact factor have brought about a decrease in number of case reports published. 5 , 10 However, journals exclusively publishing case reports have been developed and include the Journal of Medical Case Reports and Clinical Case Reports. These journals recognize the importance and need for case report literature. 11 Despite the need for well-designed studies, case reports have provided significant information that has helped to advance medical treatment. 5–7 Case reports have been found to be a viable source for identifying unexpected or uncommon occurrences, previously unknown conditions, new adverse drug reactions (ADRs), and innovative indications for medications. 9 This chapter will provide a description of case reports and case series including, for each, a definition, characteristics, study design features, writing guidelines, strengths/limitations, and points for critical evaluation.

Case Report Definition

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A case report is a detailed report of the diagnosis, treatment, response to treatment, and follow-up after treatment of an individual patient. A case series is group of case reports involving patients who were given similar treatment. Case reports and case series usually contain demographic information about the patient(s), for example, age, gender, ethnic origin.

When information on more than three patients is included, the case series is considered to be a systematic investigation designed to contribute to generalizable knowledge (i.e., research ), and therefore submission is required to the IRB.

For all case reports and case series, a signed HIPAA authorization should be obtained from the patients or their legally authorized representatives for the use and disclosure of their Protected Health Information. The only exception to the requirement for obtaining authorization is if the author of a case report or case series believes that the information is not identifiable; in this case, the author must consult with the Privacy Officer at Boston Medical Center ( [email protected] ) or the HIPAA Privacy Officer of Boston University ( [email protected] ) to seek an expert opinion about the magnitude of the risk of identifying an individual.

For case reports or case series containing more than three patients, the HIPAA authorization should be part of the consent form that is reviewed by the IRB.

For case reports or case series containing three or fewer patients, authors should prepare an authorization form using the following templates and arrange for review as indicated below. The red text in the template should be customized for the specific case report or case series. Please note that for deceased patients, authorization must be obtained from the personal representative, who is the administrator or executor of the patient’s estate.

• Boston Medical Center ( BMC Case Report HIPAA Authorization Template ) – review by the Privacy Officer at Boston Medical Center ( [email protected] ); a copy of the authorization must be filed in each patient’s medical record.
• Goldman School of Dental Medicine ( GSDM Case Report HIPAA Authorization Template ) – review by the HIPAA Privacy Officer of Boston University ( [email protected] )

Case report and case series

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Clinical "case series": a concept analysis

Affiliation.

• 1 Trauma Research Group, Faculty of Medicine and Health Sciences, UAE University, Al-Ain, UAE. [email protected]
• PMID: 23515566
• PMCID: PMC3598300

Objectives: To analyze the concept of "case series" in the medical literature compared with case reports.

Methods: A PubMed search for articles published during 2009 which had "case series" in their title was performed. A total number of 621 articles were retrieved. 586 papers were included in the analysis and 35 were excluded (18 were commentary letters, 5 were not in English, and twelve could not be retrieved by our Library). The number of patients and category of these articles were analyzed.

Results: The median (range) of the number of cases of articles having "case series" in their title was 7 (1-6432) cases. 186/ 586 articles had less than 5 cases (31.7%, 95% CI (28.3-35.1%)). The median (range) of the number of cases of articles having "case report" as their publication type was 4 (1-178) cases. Out of the 219 articles categorized as case reports 114 (52.1%, 95% CI (45.6-58.6%)) had less than five cases.

Conclusions: The concept of "case series" is not well defined in the literature and does not reflect a specific research design. We suggest that a case series should have more than four patients while four paitents or less should be reported individually as case reports.

Keywords: Case report; case series; concept analysis; research design.

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• Self controlled case...

Self controlled case series methods: an alternative to standard epidemiological study designs

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• Peer review
• Irene Petersen , reader in statistics and epidemiology 1 2 ,
• Ian Douglas , senior lecturer in pharmacoepidemiology 3 ,
• Heather Whitaker , senior lecturer in statistics 4
• 1 Department of Primary Care and Population Health, University College London, London NW3 2PF, UK
• 2 Department of Clinical Epidemiology, Aarhus University, Aarhus N, Denmark
• 3 London School of Hygiene and Tropical Medicine, London, UK
• 4 Department of Mathematics and Statistics, Open University, Milton Keynes, UK
• Correspondence to: I Petersen i.petersen{at}ucl.ac.uk
• Accepted 24 July 2016

The self controlled case series (SCCS) method is an epidemiological study design for which individuals act as their own control—ie, comparisons are made within individuals. Hence, only individuals who have experienced an event are included and all time invariant confounding is eliminated. The temporal association between a transient exposure and an event is estimated. SCCS was originally developed for evaluation of vaccine safety, but has since been applied in a range of settings where exact information on the size of the population at risk is lacking or identification of an appropriate comparison group is difficult—eg, for studies of adverse effects of drug treatments. We provide an overview of the SCCS method, with examples of its use, discuss limitations, assumptions, and potential biases that can arise where assumptions are not met, and provide solutions and examples of good practice.

Summary points

The self controlled case series (SCCS) method provides an alternative to established epidemiological designs

SCCS is best suited to acute recurrent or non-recurrent events and transient exposures for which precise timings are available

Estimation is within individuals and no separate controls are required, hence the method is self controlled, and time invariant factors are cancelled out

Follow-up is not censored at the event, so when events can impact on subsequent exposure, care must be taken to ensure analyses are carried out that eliminate or minimise bias

In 1951, Richard Doll and Austin Bradford Hill wrote to all registered doctors in the United Kingdom to obtain information about their smoking habits. This research was groundbreaking as they were one of the first teams to demonstrate a link between smoking and various diseases. 1 Since then, epidemiological study designs, such as cohort and case-control studies, have been widely applied in medical research (see supplementary web table w1). There are several situations, however, where standard epidemiological study designs fall short. For example, in the research of adverse effects of vaccines it can be difficult to identify suitable comparison groups (eg, if most of the population receives the vaccine). Likewise, studies on hospital data may not have information on the exact catchment areas and hence it is a struggle to find suitable controls for cases of a particular event. In these situations the self controlled case series (SCCS) method provides an alternative epidemiological study design to investigate the association between a transient exposure and an outcome event. The SCCS method is a case only method; it has the advantages that no separate controls are required and any fixed confounder is automatically controlled for. 2 3

In this paper we provide an overview of SCCS methodology and some examples of how the method has been applied, in order to give an idea of the potentials of SCCS. As for any epidemiological study design, the SCCS method has some assumptions. We discuss these and identify the key limitations and potential biases.

SCCS method

The SCCS method aims to estimate a relative incidence, which compares the incidence of adverse events within periods of hypothesised excess risk due to exposure with incidence during all other times. Asking “when?” rather than “who?” becomes the key question. Precise timings are needed, so the SCCS method is best suited to acute events and transient exposures for which periods of exposure risk can be clearly defined. Only those who have experienced an event (cases) can contribute any information on when the event occurred, so only data on these individuals need to be collected.

Having identified cases, the next step in setting up the data for SCCS is to define observation periods—these are the study periods for each individual, over which a full history on the timing of events and exposures are available. The third step is to define the periods when exposure may have had an impact within the observation period, eg, a fixed number of days after receipt of a first drug prescription or a vaccine; these are known as exposure risk periods. All remaining time within the observation period constitutes baseline exposure periods, to which the exposure risk periods will be compared. Studies using SCCS might include multiple exposure risk periods as it may be necessary to capture either multiple doses or varying exposure related risk using several risk periods (which may be of the same or different lengths). Observation periods can be further divided according to age groups or seasons, or any other relevant time varying factors so they can be accounted for in the analysis. The fourth step is to “map” events in relation to the different periods identified. Once the data are set up, the final step is to estimate the relative incidence of events in prespecified exposure risk periods compared with baseline periods, while taking into account the effect of any time varying confounders such as age groups (see supplementary file).

In figure 1 ⇓ we illustrate the SCCS set up for someone with two exposure risk periods and five age groups (panel A) and use this individual to illustrate the output of an SCCS model (panels B to D).

Fig 1  Illustration of SCCS model output using a hypothetical individual with two exposure risk periods and five age groups. (Panel A) An individual observation period segmented by two exposure risk periods (red boxes, labelled exposure risk status 1) and five age groups (blue boxes, labelled 0 to 4). Baseline categories for age and exposure are labelled age group 0 and exposure risk status 0, respectively. (Panel B) Exposure related relative incidences. Note for the baseline category the relative incidence is 1 and the exposure relative incidence is arbitrarily set to 1.8. (Panel C) Age related relative incidence on age groups 1-4 compared with age group 0. The age relative incidences for age groups 1-4 have been set to 2, 1.5, 1.2, and 0.5, respectively. (Panel D) Overall profile of relative incidence on each of the nine intervals; this is the age related relative incidence multiplied by the exposure related relative incidence

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Comparisons are not made between individuals as in a cohort or case-control study; estimation is within individuals. Any factor or characteristic that remains constant over observation periods cancels out of the SCCS model; this includes individual specific underlying risk and factors such as sex, ethnicity, and deprivation. It is in this sense that the SCCS model is self controlled.

Conceptually, the SCCS method builds on the principles of a cohort study (see supplementary file). Individuals are followed through time, the exposure history is fixed, and events are random. However, the SCCS method differs in that the total number of events occurring within an individual’s observation period is fixed and follow-up is not censored at an event. Hence all exposures occurring within the observation period—both before and after individuals have experienced the event—are included in the analysis.

A worked example that illustrates how to fit the SCCS model is included in the supplementary materials, and further details of the theory and model fitting are given in Whitaker et al. 3 Below we present two examples of studies that applied the SCCS method. Figure 2 ⇓ provides a schematic overview of the SCCS study design for each of the studies, and the key results.

Fig 2  Typical observation periods, risk periods, and headline results for two examples of applied SCCS. PPI=proton pump inhibitor

Example applications of the SCCS method in medical research

Example 1: a possible drug interaction between clopidogrel and proton pump inhibitors.

Douglas et al used both a cohort and an SCCS approach to study a drug interaction between clopidogrel and proton pump inhibitors on the risk of myocardial infarction. 4 The cohort analysis found an increased risk of myocardial infarction when clopidogrel was combined with a proton pump inhibitor, supporting the notion that an interaction between the two drugs would reduce the effectiveness of clopidogrel (relative incidence 1.30, 95% confidence interval 1.12 to 1.50). However, the effect was non-specific, as an increased risk of death from non-vascular causes was also seen, suggesting it was difficult to account for underlying confounding. The SCCS analysis examined whether the risk of myocardial infarction was increased in the period when the proton pump inhibitor was added to clopidogrel treatment (fig 2 ⇑ ). Thus the observation period was the duration of clopidogrel treatment, and the exposure risk periods were periods of proton pump inhibitor treatment, which varied in length and number among the study participants. SCCS found no increased risk for myocardial infarction (0.75, 0.55 to 1.01), suggesting that the underlying confounding had been dealt with through this design.

Example 2: inflammations and myocardial infarction or stroke

Smeeth et al aimed to evaluate the association between inflammation and myocardial infarction or stroke. 5 The exposures included inflammatory stimuli: vaccinations and acute infection. SCCS was used because of concerns that people receiving vaccinations may differ from those who were unvaccinated, and likewise, people acquiring infections may differ from uninfected people in ways that are difficult to measure and account for. Exposure risk periods were defined up to 91 days after the recording of either an infection or a vaccination and were further subdivided to allow the relative incidence of events to vary over this period (fig 2 ⇑ ). An increased risk of both myocardial infarction and stroke was seen over the risk period after either a systemic respiratory tract infection or a urinary tract infection, with the strongest effect in the first seven days. The risk was still increased up to 91 days, but appeared to be returning towards baseline. No increased risk was seen after influenza, tetanus, or pneumococcal vaccinations. 5 Figure 2 ⇑ provides the incidence rate ratios for myocardial infarction after respiratory tract infections.

SCCS assumptions

As for other epidemiological study designs, the SCCS model makes certain assumptions that should be met to provide valid and unbiased estimates. Below we outline these assumptions. Table 1 ⇓ provides a summary of assumption violations that can arise, and the solutions and examples of good practice against each.

Violation of assumptions, impact, and solutions with examples of good practice

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Occurrence of an event should not (appreciably) affect subsequent exposures

A key assumption is that subsequent exposures should not appreciably be affected by previous events. However, this may often be the case. For example, occurrence of an event may delay exposure, the event may be a contraindication for treatment, or the event may result in or is death. This assumption also means that the event itself should not determine the timing of the end of the observation period.

Ignoring this assumption may potentially produce biased estimates, but there are various extensions or moderations to the SCCS method that can mitigate potential biases (table 1 ⇑ ). Note that independent causes of death or end of observation do not cause bias.

Temporary delay or increase in exposure after an event

If the event only temporarily delays exposure this will result in a deficit of events in the period just before exposure that reduces the overall incidence in the baseline period. This results in relative incidence estimates that are biased upwards. One way to correct for this bias is to include a “pre-exposure period” (table 1 ⇑ ) just before an exposure. 3 A pre-exposure period can similarly be applied if there is a short term increase in the probability of exposure after an event (table 1 ⇑ ), which would otherwise bias estimates towards the null. A pre-exposure period was included in the clopidogrel and proton pump inhibitor interaction example, anticipating that the chance of starting treatment with a proton pump inhibitor could be temporarily altered by having a myocardial infarction (fig 2 ⇑ ). 4 The pre-exposure period “trick” only works for short term delay (in relation to the length of observation). If there is a long term delay in exposure after events, the methods in the next paragraph may be applied.

No exposure can occur after the event, eg, if the outcome is death

If the outcome is death, then exposures that might have otherwise occurred after the event will never be known. This is also true if the exposure history is only collected up until the time of the event or if the event is a contraindication to exposure (table 1 ⇑ ). If a fixed length exposure can only occur once, a simple solution is to define the observation to begin with the start of exposure and finish with the end of study that would have applied had death or censoring not occurred. 3 8 This a priori definition of the observation period means that only exposed cases are included, and if the exposure risk period is of a fixed length then the full exposure history is always known even beyond the time of death or censoring. Alternatively, there is an extension of the SCCS method that produces unbiased estimates given these scenarios. 9

If the outcome is death, but the exposure is external to the case and fully observable after death—eg, a weather phenomenon—the standard SCCS method can be applied using the full planned observation period, had the case not died.

Event increases the probability of death

If the event carries high mortality, such as myocardial infarction or stroke, then there is a chance that observation periods could be cut short as a direct result of the event. Resulting bias can be in either direction (table 1 ⇑ ). If the event mortality is low, bias will be negligible and the situation ignorable. Comparison of results from fitting SCCS models to all cases and excluding those who died can be made; major differences would suggest bias. Bias may be corrected by fitting an extension that involves modelling post-event survival times. 12

Event rates are constant within intervals

Event rates are assumed to be constant within each defined period. While such an assumption is often unrealistic, it is convenient, makes relative incidence estimates easy to interpret, and is commonly used in other study designs. Control of strong age or season effects is important and SCCS models with greater flexibility have been developed. 14 15

Events must be independently recurrent or rare

The SCCS method was developed for independent recurrent events, but it has been demonstrated that the method is valid for non-recurrent events when the risk of occurrence over the study period in the entire cohort is 10% or less. 12 A test for independence has been developed. 16 If events are dependent, a simple solution is to study just first events (table 1 ⇑ ). Alternatively, an extension that allows a first event to increase the future event risk may be used 17

Final remarks

With this paper we have sought to demonstrate how the SCCS method provides an alternative to standard epidemiological designs when investigating associations between a transient exposure and an outcome event. A major strength of the SCCS is that it is self controlled and accounts for any factor or characteristic that remains constant over the observation period. Thus, where uncertainty over the control of fixed confounders exists in a cohort or case-control study, SCCS may provide a superior design, given careful thought is made to applying the methodology correctly.

Linked information

The Open University hosts a website for the SCCS methodology, with example datasets and code for analysis in Stata, SAS, R, Genstat, and GLIM ( http://statistics.open.ac.uk/sccs )

A link to the tutorial by Whitaker et al 3 can also be found at http://statistics.open.ac.uk/sccs/sccs.pdf

Contributors: IP, ID, and HW jointly wrote this paper. HW is a leading expert in SCCS and has been involved in the development of the SCCS methodology from 2004 and onwards. ID and IP have applied the SCCS in a range of settings and encourage colleagues and students to consider the application of SCCS in (pharmaco)-epidemiological studies. HW is the guarantor.

Funding: HW was supported by an Medical Research Council methodology grant (MR/L009005/1).

Competing interests: We have read and understood the BMJ policy on declaration of interests and declare the following: none.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/3.0/ .

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