Study Design

Study Design US Medical PG Question 1: A study is funded by the tobacco industry to examine the association between smoking and lung cancer. They design a study with a prospective cohort of 1,000 smokers between the ages of 20-30. The length of the study is five years. After the study period ends, they conclude that there is no relationship between smoking and lung cancer. Which of the following study features is the most likely reason for the failure of the study to note an association between tobacco use and cancer?

• A. Late-look bias
• B. Latency period (Correct Answer)
• C. Confounding
• D. Effect modification
• E. Pygmalion effect

Study Design Explanation: ***Latency period*** - **Lung cancer** typically has a **long latency period**, often **20-30+ years**, between initial exposure to tobacco carcinogens and the development of clinically detectable disease. - A **five-year study duration** in young smokers (ages 20-30) is **far too short** to observe the development of lung cancer, which explains the false negative finding. - This represents a **fundamental flaw in study design** rather than a bias—the biological timeline of disease development was not adequately considered. *Late-look bias* - **Late-look bias** occurs when a study enrolls participants who have already survived the early high-risk period of a disease, leading to **underestimation of true mortality or incidence**. - Also called **survival bias**, it involves studying a population that has already been "selected" by survival. - This is not applicable here, as the study simply ended before sufficient time elapsed for disease to develop. *Confounding* - **Confounding** occurs when a third variable is associated with both the exposure and outcome, distorting the apparent relationship between them. - While confounding can affect study results, it would not completely eliminate the detection of a strong, well-established association like smoking and lung cancer in a properly conducted prospective cohort study. - The issue here is temporal (insufficient follow-up time), not the presence of an unmeasured confounder. *Effect modification* - **Effect modification** (also called interaction) occurs when the magnitude of an association between exposure and outcome differs across levels of a third variable. - This represents a **true biological phenomenon**, not a study design flaw or bias. - It would not explain the complete failure to detect any association. *Pygmalion effect* - The **Pygmalion effect** (observer-expectancy effect) refers to a psychological phenomenon where higher expectations lead to improved performance in the observed subjects. - This concept is relevant to **behavioral and educational research**, not to objective epidemiological studies of disease incidence. - It has no relevance to the biological relationship between carcinogen exposure and cancer development.

Study Design US Medical PG Question 2: A research team develops a new monoclonal antibody checkpoint inhibitor for advanced melanoma that has shown promise in animal studies as well as high efficacy and low toxicity in early phase human clinical trials. The research team would now like to compare this drug to existing standard of care immunotherapy for advanced melanoma. The research team decides to conduct a non-randomized study where the novel drug will be offered to patients who are deemed to be at risk for toxicity with the current standard of care immunotherapy, while patients without such risk factors will receive the standard treatment. Which of the following best describes the level of evidence that this study can offer?

• A. Level 1
• B. Level 3 (Correct Answer)
• C. Level 5
• D. Level 4
• E. Level 2

Study Design Explanation: ***Level 3*** - A **non-randomized controlled trial** like the one described, where patient assignment to treatment groups is based on specific characteristics (risk of toxicity), falls into Level 3 evidence. - This level typically includes **non-randomized controlled trials** and **well-designed cohort studies** with comparison groups, which are prone to selection bias and confounding. - The study compares two treatments but lacks randomization, making it Level 3 evidence. *Level 1* - Level 1 evidence is the **highest level of evidence**, derived from **systematic reviews and meta-analyses** of multiple well-designed randomized controlled trials or large, high-quality randomized controlled trials. - The described study is explicitly stated as non-randomized, ruling out Level 1. *Level 2* - Level 2 evidence involves at least one **well-designed randomized controlled trial** (RCT) or **systematic reviews** of randomized trials. - The current study is *non-randomized*, which means it cannot be classified as Level 2 evidence, as randomization is a key criterion for this level. *Level 4* - Level 4 evidence includes **case series**, **case-control studies**, and **poorly designed cohort or case-control studies**. - While the study is non-randomized, it is a controlled comparative trial rather than a case series or retrospective case-control study, placing it at Level 3. *Level 5* - Level 5 evidence is the **lowest level of evidence**, typically consisting of **expert opinion** without explicit critical appraisal, or based on physiology, bench research, or animal studies. - While the drug was initially tested in animal studies, the current human comparative study offers a higher level of evidence than expert opinion or preclinical data.

Study Design US Medical PG Question 3: A researcher is conducting a study to compare fracture risk in male patients above the age of 65 who received annual DEXA screening to peers who did not receive screening. He conducts a randomized controlled trial in 900 patients, with half of participants assigned to each experimental group. The researcher ultimately finds similar rates of fractures in the two groups. He then notices that he had forgotten to include 400 patients in his analysis. Including the additional participants in his analysis would most likely affect the study's results in which of the following ways?

• A. Wider confidence intervals of results
• B. Increased probability of committing a type II error
• C. Decreased significance level of results
• D. Increased external validity of results
• E. Increased probability of rejecting the null hypothesis when it is truly false (Correct Answer)

Study Design Explanation: ***Increased probability of rejecting the null hypothesis when it is truly false*** - Including more participants increases the **statistical power** of the study, making it more likely to detect a true effect if one exists. - A higher sample size provides a more precise estimate of the population parameters, leading to a greater ability to **reject a false null hypothesis**. *Wider confidence intervals of results* - A larger sample size generally leads to **narrower confidence intervals**, as it reduces the standard error of the estimate. - Narrower confidence intervals indicate **greater precision** in the estimation of the true population parameter. *Increased probability of committing a type II error* - A **Type II error** (false negative) occurs when a study fails to reject a false null hypothesis. - Increasing the sample size typically **reduces the probability of a Type II error** because it increases statistical power. *Decreased significance level of results* - The **significance level (alpha)** is a pre-determined threshold set by the researcher before the study begins, typically 0.05. - It is independent of sample size and represents the **acceptable probability of committing a Type I error** (false positive). *Increased external validity of results* - **External validity** refers to the generalizability of findings to other populations, settings, or times. - While a larger sample size can enhance the representativeness of the study population, external validity is primarily determined by the **sampling method** and the study's design context, not just sample size alone.

Study Design US Medical PG Question 4: You are reading through a recent article that reports significant decreases in all-cause mortality for patients with malignant melanoma following treatment with a novel biological infusion. Which of the following choices refers to the probability that a study will find a statistically significant difference when one truly does exist?

• A. Type II error
• B. Type I error
• C. Confidence interval
• D. p-value
• E. Power (Correct Answer)

Study Design Explanation: ***Power*** - **Power** is the probability that a study will correctly reject the null hypothesis when it is, in fact, false (i.e., will find a statistically significant difference when one truly exists). - A study with high power minimizes the risk of a **Type II error** (failing to detect a real effect). *Type II error* - A **Type II error** (or **beta error**) occurs when a study fails to reject a false null hypothesis, meaning it concludes there is no significant difference when one actually exists. - This is the **opposite** of what the question describes, which asks for the probability of *finding* a difference. *Type I error* - A **Type I error** (or **alpha error**) occurs when a study incorrectly rejects a true null hypothesis, concluding there is a significant difference when one does not actually exist. - This relates to the **p-value** and the level of statistical significance (e.g., p < 0.05). *Confidence interval* - A **confidence interval** provides a range of values within which the true population parameter is likely to lie with a certain degree of confidence (e.g., 95%). - It does not directly represent the probability of finding a statistically significant difference when one truly exists. *p-value* - The **p-value** is the probability of observing data as extreme as, or more extreme than, that obtained in the study, assuming the null hypothesis is true. - It is used to determine statistical significance, but it is not the probability of detecting a true effect.

Study Design US Medical PG Question 5: Which of the following study designs would be most appropriate to investigate the association between electronic cigarette use and the subsequent development of lung cancer?

• A. Subjects with lung cancer who smoke and subjects with lung cancer who did not smoke
• B. Subjects who smoke electronic cigarettes and subjects who smoke normal cigarettes
• C. Subjects with lung cancer who smoke and subjects without lung cancer who smoke
• D. Subjects with lung cancer and subjects without lung cancer
• E. Subjects who smoke electronic cigarettes and subjects who do not smoke (Correct Answer)

Study Design Explanation: ***Subjects who smoke electronic cigarettes and subjects who do not smoke*** - This design represents a **cohort study**, which is ideal for investigating the **incidence** of a disease (lung cancer) in groups exposed and unexposed to a risk factor (electronic cigarette use). - By following these two groups over time, researchers can directly compare the **risk of developing lung cancer** in e-cigarette users versus non-smokers. *Subjects with lung cancer who smoke and subjects with lung cancer who did not smoke* - This option incorrectly compares two groups both with lung cancer, where the exposure to smoking can either be **electronic or traditional cigarettes,** but does not provide a control group without lung cancer to assess the association. - This design would not allow for the calculation of an **incidence rate** or a **relative risk** of lung cancer development specific to electronic cigarette use. *Subjects who smoke electronic cigarettes and subjects who smoke normal cigarettes* - This design compares two different types of smoking, which might be useful for comparing their relative risks but doesn't include a **non-smoking control group** to establish the absolute association with electronic cigarettes. - While it could show if e-cigarettes are "safer" than traditional cigarettes, it wouldn't directly answer whether e-cigarettes themselves **cause lung cancer**. *Subjects with lung cancer who smoke and subjects without lung cancer who smoke* - This describes a **case-control study** but focuses on smoking in general rather than specifically electronic cigarettes, which is the independent variable of interest. - While valuable for identifying risk factors, it would need to specifically differentiate between **electronic cigarette smokers** and other smokers to answer the question adequately. *Subjects with lung cancer and subjects without lung cancer* - This general description of a **case-control study** is too broad; it does not specify the exposure of interest, which is electronic cigarette use. - To be relevant, the study would need to gather data on **electronic cigarette use** in both the lung cancer group and the non-lung cancer control group.

Study Design Flashcard 1 of 5

Question: _____ studies are observational studies that compare a group of people with disease to a group without disease

Answer: Case-control

Study Design Flashcard 2 of 5

Question: What type of study uses subjects as their own controls?_____

Answer: Crossover studies

Study Design Flashcard 3 of 5

Question: Confounding bias occurs when the exposure-disease relationship is muddled by the effect of an extraneous factor that is associated with both exposure and disease and _____ on the causal pathway

Answer: is NOT

Study Design Flashcard 4 of 5

Question: A method of statistical analysis that pools summary data (ex. means, RRs) from multiple studies for a more precise estimate of the size of an effect is known as _____

Answer: meta-analysis

Study Design Flashcard 5 of 5

Question: Which type of observational study is best for studying rare diseases? _____

Answer: Case-control studies