I'm designing a case-control study. Help me: 1) Define cases with clear criteria

Prompt
I'm designing a case-control study. Help me: 1) Define cases with clear criteria
ChatGPTOpenAI
I'm designing a case-control study. Help me: 1) Define cases with clear criteria

Defining cases in a case-control study is a critical step to ensure the study's validity and reliability. Here are some steps and considerations to help you systematically define your cases:

1. Identify the Disease or Condition of Interest


  • Clearly define the health outcome or condition that the cases will have. This could be a specific disease (e.g., type 2 diabetes, breast cancer), a clinical condition (e.g., heart failure), or an event (e.g., myocardial infarction).


2. Establish Diagnostic Criteria


  • Use objective, standardized criteria to define what constitutes a "case." This could include:

  • Clinical Diagnosis: Use established clinical guidelines for diagnosis. For example, in diabetes studies, use the American Diabetes Association (ADA) criteria.

  • Laboratory Tests: Require specific test results (e.g., a glycated hemoglobin level > 6.5% for diabetes).

  • Imaging Findings: For conditions like certain cancers, define cases based on radiological evidence (e.g., presence of a tumor as seen on MRI).

  • Pathological Confirmation: For some conditions, a biopsy or other pathological assessment may be required for diagnosis.


3. Define the Time Frame


  • Specify the time frame for case eligibility (e.g., diagnosis must occur within the last 5 years). This helps capture incident cases rather than prevalent cases, depending on your study design.


4. Inclusion Criteria


  • Define clear inclusion criteria, which could include:

  • Age range

  • Gender

  • Geographic location

  • Other demographic factors (e.g., ethnicity) as relevant to the condition and study goals.


5. Exclusion Criteria


  • Establish exclusion criteria to rule out cases that may confound your study results. Common exclusions might include:

  • Cases with a secondary etiology for the condition.

  • Previous treatment that may impact the outcome.

  • Comorbid conditions that complicate interpretation of results.


6. Method of Case Ascertainment


  • Determine how cases will be identified. Possible methods include:

  • Clinic or hospital records

  • Disease registries

  • Surveys or interviews with patients

  • Collaboration with healthcare providers or organizations.


7. Ensure Feasibility and Ethical Considerations


  • Consider logistical aspects such as the availability of cases, resources for case identification, and ethical implications related to patient confidentiality in your design.


Example Case Definition


If your study focuses on type 2 diabetes, a sample case definition might be:

Cases: Adult individuals aged 30-75 years diagnosed with type 2 diabetes as defined by any of the following criteria within the last 5 years:

  • Fasting plasma glucose of 126 mg/dL (7.0 mmol/L) or greater.

  • A 2-hour plasma glucose of 200 mg/dL (11.1 mmol/L) or greater during an oral glucose tolerance test.

  • A hemoglobin A1c level of 6.5% (48 mmol/mol) or greater.

  • A physician’s diagnosis documented in medical records, confirmed by an endocrinologist.


By systematically defining the cases using these criteria, you'll enhance the validity and reliability of your case-control study.

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ClaudeAnthropic
I'm designing a case-control study. Help me: 1) Define cases with clear criteria

Defining Cases for Your Case-Control Study

Key Principles for Case Definition

A strong case definition should be:

  • Specific: Clear diagnostic criteria that minimize misclassification

  • Objective: Based on verifiable evidence (lab tests, imaging, medical records)

  • Incident vs. Prevalent: Decide whether to include newly diagnosed cases only or all existing cases

  • Time-bound: Specify the time period for case identification


Essential Components of Your Case Definition

1. Diagnostic Criteria


  • What specific disease/condition are you studying?

  • Use standardized diagnostic criteria (e.g., ICD codes, clinical guidelines, validated scoring systems)

  • Specify whether diagnosis requires:

  • Laboratory confirmation

  • Imaging findings

  • Clinical symptoms

  • Pathology results

  • Combinations of the above


2. Inclusion Criteria


  • Age range

  • Geographic location

  • Time period of diagnosis

  • Disease stage/severity (if relevant)

  • Minimum diagnostic certainty required


3. Exclusion Criteria


  • Conditions that might confound the exposure-outcome relationship

  • Patients with unclear diagnosis

  • Secondary cases (if studying primary disease)

  • Pre-existing conditions that would affect exposure assessment


4. Source of Case Identification


  • Hospital registries

  • Disease surveillance systems

  • Medical records databases

  • Death certificates (for fatal conditions)

  • Specialty clinics


Example Template

"Cases are defined as individuals who:

  • [Specific diagnosis]

  • Diagnosed between [dates]

  • Aged [range]

  • Confirmed by [diagnostic method]

  • Identified from [source]

  • With no history of [exclusions]"


Would you like help with controls, matching strategy, or exposure assessment next?
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Analysis

This comparison demonstrates the different approaches each AI model takes when responding to the same prompt. Here are the key differences observed:

Response Characteristics

ChatGPT: Provides a direct response with 49 sentences.

Claude: Provides a detailed response with 9 sentences.

Key Takeaways

  • Each model brings unique strengths to this type of query
  • Response styles vary significantly between models
  • Consider your specific use case when choosing between these models

Try This Comparison Yourself

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This comparison was generated using the SNEOS AI Comparison ToolPublished: October 15, 2025 | Models: ChatGPT, Claude