Follow-up methods US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Follow-up methods. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Follow-up methods US Medical PG Question 1: A researcher is studying whether a new knee implant is better than existing alternatives in terms of pain after knee replacement. She designs the study so that it includes all the surgeries performed at a certain hospital. Interestingly, she notices that patients who underwent surgeries on Mondays and Thursdays reported much better pain outcomes on a survey compared with those who underwent the same surgeries from the same surgeons on Tuesdays and Fridays. Upon performing further analysis, she discovers that one of the staff members who works on Mondays and Thursdays is aware of the study and tells all the patients about how wonderful the new implant is. Which of the following forms of bias does this most likely represent?
- A. Hawthorne effect
- B. Pygmalion effect (Correct Answer)
- C. Attrition bias
- D. Golem effect
Follow-up methods Explanation: ***Pygmalion effect***
- This bias occurs when higher expectations lead to an increase in performance. In this scenario, the staff member's positive reinforcement about the new implant likely instilled **higher patient expectations**, leading to better reported pain outcomes.
- The patients' belief in the implant's superiority, influenced by the staff member, acted as a **self-fulfilling prophecy**, improving their subjective pain experience.
*Hawthorne effect*
- This effect describes how individuals modify an aspect of their behavior in response to their awareness of being observed. While patients were part of a study, their improved outcomes were specifically linked to a staff member's verbal influence, not solely the act of observation.
- The improved pain outcomes stem from the **expectations created by the staff member's praise**, rather than a general awareness of being studied.
*Attrition bias*
- Attrition bias refers to systematic differences between groups in the loss of participants from a study.
- This scenario describes differences in patient outcomes based on staff influence during the study, not due to **patients dropping out differentially** between groups.
*Golem effect*
- The Golem effect is the opposite of the Pygmalion effect, where lower expectations placed upon individuals lead to poorer performance from them.
- In this case, the staff member's influence created **high expectations and positive outcomes**, not negative expectations leading to worse outcomes.
Follow-up methods US Medical PG Question 2: 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)
Follow-up methods 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.
Follow-up methods US Medical PG Question 3: An investigator is measuring the blood calcium level in a sample of female cross country runners and a control group of sedentary females. If she would like to compare the means of the two groups, which statistical test should she use?
- A. Chi-square test
- B. Linear regression
- C. t-test (Correct Answer)
- D. ANOVA (Analysis of Variance)
- E. F-test
Follow-up methods Explanation: ***t-test***
- A **t-test** is appropriate for comparing the means of two independent groups, such as the blood calcium levels between runners and sedentary females.
- It assesses whether the observed difference between the two sample means is statistically significant or occurred by chance.
*Chi-square test*
- The **chi-square test** is used to analyze categorical data to determine if there is a significant association between two variables.
- It is not suitable for comparing continuous variables like blood calcium levels.
*Linear regression*
- **Linear regression** is used to model the relationship between a dependent variable (outcome) and one or more independent variables (predictors).
- It aims to predict the value of a variable based on the value of another, rather than comparing means between groups.
*ANOVA (Analysis of Variance)*
- **ANOVA** is used to compare the means of **three or more independent groups**.
- Since there are only two groups being compared in this scenario, a t-test is more specific and appropriate.
*F-test*
- The **F-test** is primarily used to compare the variances of two populations or to assess the overall significance of a regression model.
- While it is the basis for ANOVA, it is not the direct test for comparing the means of two groups.
Follow-up methods US Medical PG Question 4: An experimental new drug (SD27C) is being studied. This novel drug delivers insulin via the intranasal route. Consent is obtained from participants who are diabetic and are taking insulin as their current treatment regimen to participate in a clinical trial. 500 patients consent and are divided into 2 groups, and a double-blind clinical trial was conducted. One group received the new formulation (SD27C), while the second group received regular insulin via subcutaneous injection. The results showed that the treatment outcomes in both groups are the same. SD27C is currently under investigation in which phase of the clinical trial?
- A. Phase II
- B. Phase III (Correct Answer)
- C. Post-market surveillance
- D. Phase I
- E. Phase IV
Follow-up methods Explanation: ***Phase III***
- **Phase III trials** involve a large number of participants (hundreds to thousands) and compare the new drug to standard treatment or placebo to assess its **efficacy** and monitor for adverse effects.
- The description of a **double-blind clinical trial** with 500 patients divided into two groups, comparing the new drug (SD27C) to regular insulin with similar treatment outcomes, is characteristic of a Phase III study.
*Phase II*
- **Phase II trials** typically involve a smaller group of patients (tens to a few hundred) to evaluate the drug's **effectiveness**, further assess safety, and determine the optimal dosage.
- The sample size of 500 patients in this scenario is too large for a typical Phase II trial.
*Post-market surveillance*
- This term is synonymous with **Phase IV trials**, which occur after the drug has been approved and marketed, focusing on long-term safety and effectiveness in a broader population.
- The drug is still "under investigation" and being compared to existing treatment, indicating it has not yet been approved.
*Phase I*
- **Phase I trials** are the initial human trials, usually involving a small number of **healthy volunteers**, to evaluate the drug's safety, dosage range, and pharmacokinetics.
- The study involves diabetic patients, not healthy volunteers, and the focus is on efficacy comparison, not just basic safety.
*Phase IV*
- **Phase IV trials** (or post-market surveillance) take place **after a drug has been approved** and marketed, monitoring its long-term effects, optimal use, and safety in a real-world setting.
- The drug is still in a comparative efficacy trial and has not yet received approval for general use.
Follow-up methods US Medical PG Question 5: In the study, all participants who were enrolled and randomly assigned to treatment with pulmharkimab were analyzed in the pulmharkimab group regardless of medication nonadherence or refusal of allocated treatment. A medical student reading the abstract is confused about why some participants assigned to pulmharkimab who did not adhere to the regimen were still analyzed as part of the pulmharkimab group. Which of the following best reflects the purpose of such an analysis strategy?
- A. To minimize type 2 errors
- B. To assess treatment efficacy more accurately
- C. To reduce selection bias (Correct Answer)
- D. To increase internal validity of study
- E. To increase sample size
Follow-up methods Explanation: ***To reduce selection bias***
- Analyzing participants in their originally assigned groups, regardless of adherence, is known as **intention-to-treat (ITT) analysis**.
- This method helps **preserve randomization** and minimizes **selection bias** that could arise if participants who did not adhere to treatment were excluded or re-assigned.
- **This is the most direct and specific purpose** of ITT analysis - preventing systematic differences between groups caused by post-randomization exclusions.
*To minimize type 2 errors*
- While ITT analysis affects statistical power, its primary purpose is not specifically to minimize **type 2 errors** (false negatives).
- ITT analysis may sometimes *increase* the likelihood of a type 2 error by diluting the treatment effect due to non-adherence.
*To assess treatment efficacy more accurately*
- ITT analysis assesses the **effectiveness** of *assigning* a treatment in a real-world setting, rather than the pure biological **efficacy** of the treatment itself.
- Efficacy is better assessed by a **per-protocol analysis**, which only includes compliant participants.
- ITT provides a more **conservative** and **pragmatic** estimate of treatment effect.
*To increase internal validity of study*
- While ITT analysis does contribute to **internal validity** by maintaining randomization, this is a **broader, secondary benefit** rather than the primary purpose.
- Internal validity encompasses many aspects of study design; ITT specifically addresses **post-randomization bias prevention**.
- The more precise answer is that ITT reduces **selection bias**, which is one specific threat to internal validity.
- Many other design features also contribute to internal validity (blinding, standardized protocols, etc.), making this option less specific.
*To increase sample size*
- ITT analysis includes all randomized participants, so it maintains the initial **sample size** that was randomized.
- However, the primary purpose is to preserve the integrity of randomization and prevent bias, not simply to increase the number of participants in the final analysis.
Follow-up methods US Medical PG Question 6: A research group wants to assess the safety and toxicity profile of a new drug. A clinical trial is conducted with 20 volunteers to estimate the maximum tolerated dose and monitor the apparent toxicity of the drug. The study design is best described as which of the following phases of a clinical trial?
- A. Phase 0
- B. Phase III
- C. Phase V
- D. Phase II
- E. Phase I (Correct Answer)
Follow-up methods Explanation: ***Phase I***
- **Phase I clinical trials** involve a small group of healthy volunteers (typically 20-100) to primarily assess **drug safety**, determine a safe dosage range, and identify side effects.
- The main goal is to establish the **maximum tolerated dose (MTD)** and evaluate the drug's pharmacokinetic and pharmacodynamic profiles.
*Phase 0*
- **Phase 0 trials** are exploratory studies conducted in a very small number of subjects (10-15) to gather preliminary data on a drug's **pharmacodynamics and pharmacokinetics** in humans.
- They involve microdoses, not intended to have therapeutic effects, and thus cannot determine toxicity or MTD.
*Phase III*
- **Phase III trials** are large-scale studies involving hundreds to thousands of patients to confirm the drug's **efficacy**, monitor side effects, compare it to standard treatments, and collect information that will allow the drug to be used safely.
- These trials are conducted after safety and initial efficacy have been established in earlier phases.
*Phase V*
- "Phase V" is not a standard, recognized phase in the traditional clinical trial classification (Phase 0, I, II, III, IV).
- This term might be used in some non-standard research contexts or for post-marketing studies that go beyond Phase IV surveillance, but it is not a formal phase for initial drug development.
*Phase II*
- **Phase II trials** involve several hundred patients with the condition the drug is intended to treat, focusing on **drug efficacy** and further evaluating safety.
- While safety is still monitored, the primary objective shifts to determining if the drug works for its intended purpose and at what dose.
Follow-up methods US Medical PG Question 7: Study X examined the relationship between coffee consumption and lung cancer. The authors of Study X retrospectively reviewed patients' reported coffee consumption and found that drinking greater than 6 cups of coffee per day was associated with an increased risk of developing lung cancer. However, Study X was criticized by the authors of Study Y. Study Y showed that increased coffee consumption was associated with smoking. What type of bias affected Study X, and what study design is geared to reduce the chance of that bias?
- A. Observer bias; double blind analysis
- B. Selection bias; randomization
- C. Lead time bias; placebo
- D. Measurement bias; blinding
- E. Confounding; randomization (Correct Answer)
Follow-up methods Explanation: ***Confounding; randomization***
- Study Y suggests that **smoking** is a **confounding variable** because it is associated with both increased coffee consumption (exposure) and increased risk of lung cancer (outcome), distorting the apparent relationship between coffee and lung cancer.
- **Randomization** in experimental studies (such as randomized controlled trials) helps reduce confounding by ensuring that known and unknown confounding factors are evenly distributed among study groups.
- In observational studies where randomization is not possible, confounding can be addressed through **stratification**, **matching**, or **multivariable adjustment** during analysis.
*Observer bias; double blind analysis*
- **Observer bias** occurs when researchers' beliefs or expectations influence the study outcome, which is not the primary issue described here regarding the relationship between coffee, smoking, and lung cancer.
- **Double-blind analysis** is a method to mitigate observer bias by ensuring neither participants nor researchers know who is in the control or experimental groups.
*Selection bias; randomization*
- **Selection bias** happens when the study population is not representative of the target population, leading to inaccurate results, which is not directly indicated by the interaction between coffee and smoking.
- While **randomization** is used to reduce selection bias by creating comparable groups, the core problem identified in Study X is confounding, not flawed participant selection.
*Lead time bias; placebo*
- **Lead time bias** occurs in screening programs when early detection without improved outcomes makes survival appear longer, an issue unrelated to the described association between coffee, smoking, and lung cancer.
- A **placebo** is an inactive treatment used in clinical trials to control for psychological effects, and its relevance here is limited to treatment intervention studies.
*Measurement bias; blinding*
- **Measurement bias** arises from systematic errors in data collection, such as inaccurate patient reporting of coffee consumption, but the main criticism from Study Y points to a third variable (smoking) affecting the association, not just flawed measurement.
- **Blinding** helps reduce measurement bias by preventing participants or researchers from knowing group assignments, thus minimizing conscious or unconscious influences on data collection.
Follow-up methods US Medical PG Question 8: A pharmaceutical corporation is developing a research study to evaluate a novel blood test to screen for breast cancer. They enrolled 800 patients in the study, half of which have breast cancer. The remaining enrolled patients are age-matched controls who do not have the disease. Of those in the diseased arm, 330 are found positive for the test. Of the patients in the control arm, only 30 are found positive. What is this test’s sensitivity?
- A. 330 / (330 + 30)
- B. 330 / (330 + 70) (Correct Answer)
- C. 370 / (30 + 370)
- D. 370 / (70 + 370)
- E. 330 / (400 + 400)
Follow-up methods Explanation: ***330 / (330 + 70)***
- **Sensitivity** measures the proportion of actual **positives** that are correctly identified as such.
- In this study, there are **400 diseased patients** (half of 800). Of these, 330 tested positive (true positives), meaning 70 tested negative (false negatives). So sensitivity is **330 / (330 + 70)**.
*330 / (330 + 30)*
- This calculation represents the **positive predictive value**, which is the probability that subjects with a positive screening test truly have the disease. It uses **true positives / (true positives + false positives)**.
- It does not correctly calculate **sensitivity**, which requires knowing the total number of diseased individuals.
*370 / (30 + 370)*
- This expression is attempting to calculate **specificity**, which is the proportion of actual negatives that are correctly identified. It would be **true negatives / (true negatives + false positives)**.
- However, the numbers used are incorrect for specificity in this context given the data provided.
*370 / (70 + 370)*
- This formula is an incorrect combination of values and does not represent any standard epidemiological measure like **sensitivity** or **specificity**.
- It is attempting to combine false negatives (70) and true negatives (370 from control arm) in a non-standard way.
*330 / (400 + 400)*
- This calculation attempts to divide true positives by the total study population (800 patients).
- This metric represents the **prevalence of true positives within the entire study cohort**, not the test's **sensitivity**.
Follow-up methods US Medical PG Question 9: A pharmaceutical company conducts a randomized clinical trial in an attempt to show that their new anticoagulant drug prevents more thrombotic events following total knee arthroplasty than the current standard of care. However, a significant number of patients are lost to follow-up or fail to complete treatment according to the study arm to which they were assigned. Several patients in the novel drug arm are also switched at a later time to a novel anticoagulant or warfarin per their primary care physician. All patients enrolled in the study are subsequently analyzed based on the initial group they were assigned to and there is a significant improvement in outcome of the new drug. What analysis most appropriately describes this trial?
- A. Per protocol
- B. As treated
- C. Non-inferiority
- D. Intention to treat (Correct Answer)
- E. Modified intention to treat
Follow-up methods Explanation: ***Intention to treat***
- **Intention-to-treat (ITT)** analysis includes all participants randomized to a treatment arm, regardless of whether they completed the intervention or switched treatments, reflecting a real-world scenario and preserving randomization benefits.
- This approach minimizes bias from **loss to follow-up** or **treatment crossovers** and provides a more conservative estimate of treatment effect.
*Per protocol*
- **Per-protocol analysis** only includes participants who completed the study exactly as planned without any deviations.
- This method is susceptible to **selection bias** because it excludes patients who may have experienced adverse events or treatment failures, potentially overestimating treatment efficacy.
*As treated*
- **As-treated analysis** analyzes patients based on the actual treatment received, rather than the treatment to which they were randomized.
- This approach can introduce **confounding** and selection bias, as patients who switch treatments may do so for reasons related to their prognosis or treatment response.
*Non-inferiority*
- A **non-inferiority trial** design aims to show that a new treatment is not appreciably worse than an active control, rather than proving superiority.
- This describes a **type of study design** or hypothesis, not an analysis method for handling patient data after randomization with non-adherence.
*Modified intention to treat*
- A **modified intention-to-treat (mITT)** analysis typically excludes a small, predefined group of patients from the ITT population, such as those who never received any study drug or were found to be ineligible after randomization.
- While similar to ITT, it involves specific exclusions that are not described in this scenario, where all randomized patients were analyzed **based on initial assignment**.
Follow-up methods US Medical PG Question 10: A researcher wants to determine whether there is an association between CRP values and the risk of MI or cancer. Four relative risk (RR) values were plotted $(0.5,1.5,1.7,1.8)$ with respect to CRP levels. What conclusion can be drawn?
- A. CRP has no relationship
- B. CRP decreases & disease decreases
- C. CRP increases disease/cancer risk (Correct Answer)
- D. No association in first interval
- E. CRP shows protective effect in first interval
Follow-up methods Explanation: ***CRP increases disease/cancer risk***
- A **relative risk (RR)** greater than 1 indicates an increased risk of the outcome (MI or cancer) in the exposed group (higher CRP levels) compared to the unexposed group.
- The plots show RRs of 1.5, 1.7, and 1.8, all of which are greater than 1, consistently indicating that higher CRP levels are associated with an elevated risk for MI or cancer.
- The overall trend across the four intervals demonstrates a positive association between CRP and disease risk.
*CRP has no relationship*
- This conclusion is incorrect because three of the four plotted RR values (1.5, 1.7, 1.8) are above 1, indicating a positive association or increased risk.
- An RR of 1 signifies no relationship, but the majority of values clearly deviate from 1, showing a definite association.
*CRP decreases & disease decreases*
- While one RR value (0.5) suggests a decreased risk, the majority of the given RRs (1.5, 1.7, 1.8) are greater than 1, indicating an increased risk.
- This option would only be true if all or most RR values were less than 1, implying a protective effect, which is not the overall trend here.
*No association in first interval*
- The first interval shows an RR of 0.5. An RR of 1 indicates no association, while an RR of 0.5 actually indicates a **decreased risk or protective effect**, rather than no association.
- Therefore, stating "no association" for the first interval is inaccurate given the definition of relative risk.
*CRP shows protective effect in first interval*
- While the first interval RR of 0.5 does suggest a protective effect in isolation, this option fails to capture the **overall conclusion** from all four data points.
- When interpreting multiple RR values together, the predominant pattern (three values >1) indicates an overall increased risk, making this a misleading conclusion for the study as a whole.
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