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In a case-control study, researchers compare individuals with a condition (cases) to those without (controls) and examine their past exposure to risk factors. If cases remember or report their exposure differently than controls—often due to the disease diagnosis influencing their memory—this introduces recall bias. This can distort the odds ratio and undermine the study’s validity.
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A nested case-control study is conducted within a pre-existing cohort. From this cohort, all individuals who develop the outcome (cases) are identified. Then, a set of matched controls—who have not developed the outcome at the time the case occurs—is selected from the same cohort.
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In a case-control study, the primary goal is to compare the exposure status of individuals with a specific outcome (cases) to those without (controls). Exposure can refer to medications, lifestyle factors, environmental risks, or medical interventions. Misclassification of exposure can lead to biased odds ratios and incorrect conclusions.
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Cancer studies often deal with rare outcomes, long latency periods, and complex exposure variables. Case-control designs offer a cost-effective, efficient solution by starting with cases (individuals diagnosed with a specific cancer) and comparing them to controls without the disease. This retrospective approach helps researchers examine potential exposures—such as lifestyle, environmental, genetic, or drug-related factors—that may contribute to cancer development.
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Rare exposures—such as niche biologics, off-label drug use, or occupational chemical exposures—are increasingly relevant in real-world evidence (RWE) generation. However, observational designs like case-control studies are less suitable for these situations unless meticulously planned. The statistical and practical constraints of identifying, measuring, and analyzing rare exposures can severely impact validity.
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In most countries, any study involving human subjects, even if observational and retrospective, must undergo ethical review. Institutional Review Boards (IRBs) or Independent Ethics Committees (IECs) assess whether the data collection process respects participant rights, privacy, and safety.
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Unlike controlled clinical trials, EHRs capture patient data in real-world clinical settings. This includes information on patient demographics, diagnoses, procedures, lab results, medications, comorbidities, and healthcare utilization.
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Each data source offers complementary strengths:
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Raw EHR data comes from diverse sources—hospital systems, outpatient clinics, specialty centers, and labs. Each source may use different formats, terminologies, and data entry practices. Standardization ensures:
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Failure to properly secure or anonymize EHR data can lead to:
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