A scientist in Chicago is studying a new blood test to detect Ab to EBV with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity much greater than what she had originally hoped for. She travels to China to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with EBV. The scientist tests these 1,200 patients' blood and finds that only 120 of them tested negative with her new exam. Of the patients who are known to be EBV-free, only 20 of them tested positive. Given these results, which of the following correlates with the exam's specificity?
Q2
A scientist in Boston is studying a new blood test to detect Ab to the parainfluenza virus with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity even greater than what she had originally hoped for. She travels to South America to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with the parainfluenza virus. The scientist tests these 1,200 patients’ blood and finds that only 120 of them tested negative with her new test. Of the following options, which describes the sensitivity of the test?
Q3
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?
Q4
A 34-year-old woman comes to a physician for a routine health maintenance examination. She moved to Denver 1 week ago after having lived in New York City all her life. She has no history of serious illness and takes no medications. Which of the following sets of changes is most likely on analysis of a blood sample obtained now compared to prior to her move?
Erythropoietin level | O2 saturation | Plasma volume
Q5
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?
Q6
An academic medical center in the United States is approached by a pharmaceutical company to run a small clinical trial to test the effectiveness of its new drug, compound X. The company wants to know if the measured hemoglobin a1c (Hba1c) of patients with type 2 diabetes receiving metformin and compound X would be lower than that of control subjects receiving only metformin. After a year of study and data analysis, researchers conclude that the control and treatment groups did not differ significantly in their Hba1c levels.
However, parallel clinical trials in several other countries found that compound X led to a significant decrease in Hba1c. Interested in the discrepancy between these findings, the company funded a larger study in the United States, which confirmed that compound X decreased Hba1c levels. After compound X was approved by the FDA, and after several years of use in the general population, outcomes data confirmed that it effectively lowered Hba1c levels and increased overall survival. What term best describes the discrepant findings in the initial clinical trial run by institution A?
Q7
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?
Q8
A research team is working on a new assay meant to increase the sensitivity of testing in cervical cancer. Current sensitivity is listed at 77%. If this research team's latest work culminates in the following results (listed in the table), has the sensitivity improved, and, if so, then by what percentage?
Research team's latest results:
| | Patients with cervical cancer | Patients without cervical cancer |
|--------------------------|-------------------------------|----------------------------------|
| Test is Positive (+) | 47 | 4 |
| Test is Negative (-) | 9 | 44 |
Q9
Two research groups independently study the same genetic variant's association with diabetes. Study A (n=5,000) reports OR=1.25, 95% CI: 1.05-1.48, p=0.01. Study B (n=50,000) reports OR=1.08, 95% CI: 1.02-1.14, p=0.006. Both studies are methodologically sound. Synthesize these findings to determine the most likely true effect and evaluate implications for clinical and research interpretation.
Q10
A prestigious journal publishes a trial showing a new cancer drug extends survival by 2 months (p=0.001, 95% CI: 1.5-2.5 months). The drug costs $150,000 per patient and causes Grade 3-4 toxicity in 60% of patients. Three prior unpublished trials showed non-significant results (all p>0.20). Synthesize these findings to evaluate the evidence base.
Correction methods (Bonferroni, FDR) US Medical PG Practice Questions and MCQs
Question 1: A scientist in Chicago is studying a new blood test to detect Ab to EBV with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity much greater than what she had originally hoped for. She travels to China to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with EBV. The scientist tests these 1,200 patients' blood and finds that only 120 of them tested negative with her new exam. Of the patients who are known to be EBV-free, only 20 of them tested positive. Given these results, which of the following correlates with the exam's specificity?
A. 82%
B. 90%
C. 84%
D. 86%
E. 98% (Correct Answer)
Explanation: ***98%***
- **Specificity** measures the proportion of **true negatives** among all actual negatives.
- In this case, 800 patients are known to be EBV-free (actual negatives), and 20 of them tested positive (false positives). This means 800 - 20 = 780 tested negative (true negatives). Specificity = (780 / 800) * 100% = **98%**.
*82%*
- This value represents the *original sensitivity* before the scientist’s new attempts to improve the test.
- It does not reflect the *newly calculated specificity* based on the provided data.
*90%*
- This value represents the *newly calculated sensitivity* of the test, not the specificity.
- Out of 1200 EBV-infected patients, 120 tested negative (false negatives), meaning 1080 tested positive (true positives). Sensitivity = (1080 / 1200) * 100% = 90%.
*84%*
- This percentage is not directly derived from the information given for either sensitivity or specificity after the new test results.
- It does not correspond to any of the calculated values for the new test's performance.
*86%*
- This percentage is not directly derived from the information given for either sensitivity or specificity after the new test results.
- It does not correspond to any of the calculated values for the new test's performance.
Question 2: A scientist in Boston is studying a new blood test to detect Ab to the parainfluenza virus with increased sensitivity and specificity. So far, her best attempt at creating such an exam reached 82% sensitivity and 88% specificity. She is hoping to increase these numbers by at least 2 percent for each value. After several years of work, she believes that she has actually managed to reach a sensitivity and specificity even greater than what she had originally hoped for. She travels to South America to begin testing her newest blood test. She finds 2,000 patients who are willing to participate in her study. Of the 2,000 patients, 1,200 of them are known to be infected with the parainfluenza virus. The scientist tests these 1,200 patients’ blood and finds that only 120 of them tested negative with her new test. Of the following options, which describes the sensitivity of the test?
A. 82%
B. 86%
C. 98%
D. 90% (Correct Answer)
E. 84%
Explanation: ***90%***
- **Sensitivity** is calculated as the number of **true positives** divided by the total number of individuals with the disease (true positives + false negatives).
- In this scenario, there were 1200 infected patients (total diseased), and 120 of them tested negative (false negatives). Therefore, 1200 - 120 = 1080 patients tested positive (true positives). The sensitivity is 1080 / 1200 = 0.90, or **90%**.
*82%*
- This value was the **original sensitivity** of the test before the scientist improved it.
- The question states that the scientist believes she has achieved a sensitivity "even greater than what she had originally hoped for."
*86%*
- This value is not directly derivable from the given data for the new test's sensitivity.
- It might represent an intermediate calculation or an incorrect interpretation of the provided numbers.
*98%*
- This would imply only 24 false negatives out of 1200 true disease cases, which is not the case (120 false negatives).
- A sensitivity of 98% would be significantly higher than the calculated 90% and the initial stated values.
*84%*
- This value is not derived from the presented data regarding the new test's performance.
- It could be mistaken for an attempt to add 2% to the original 82% sensitivity, but the actual data from the new test should be used.
Question 3: 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)
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.
Question 4: A 34-year-old woman comes to a physician for a routine health maintenance examination. She moved to Denver 1 week ago after having lived in New York City all her life. She has no history of serious illness and takes no medications. Which of the following sets of changes is most likely on analysis of a blood sample obtained now compared to prior to her move?
Erythropoietin level | O2 saturation | Plasma volume
A. ↑ unchanged unchanged
B. ↑ ↓ ↓ (Correct Answer)
C. Unchanged ↓ unchanged
D. ↓ unchanged ↑
E. Unchanged unchanged ↓
Explanation: ***↑ ↓ ↓***
- Moving to a high altitude like Denver (from sea level NYC) leads to **hypoxia**, which triggers increased **erythropoietin (EPO)** production to stimulate red blood cell formation.
- The immediate physiological response to high altitude is a **decrease in arterial PO2** and thus **oxygen saturation**, along with a **reduction in plasma volume** due to increased diuresis and fluid shifts.
*↑ unchanged unchanged*
- While **erythropoietin** would increase due to hypoxia at higher altitudes, **oxygen saturation** would decrease, not remain unchanged.
- **Plasma volume** also tends to decrease acutely at high altitudes, rather than staying unchanged.
*Unchanged ↓ unchanged*
- **Erythropoietin** would be expected to increase, not remain unchanged, as a compensatory mechanism to hypoxia.
- While **oxygen saturation** would decrease, **plasma volume** typically decreases acutely, not remaining unchanged.
*↓ unchanged ↑*
- **Erythropoietin** would increase, not decrease, in response to the lower atmospheric oxygen.
- Both **oxygen saturation** and **plasma volume** would decrease, not remain unchanged or increase, respectively.
*Unchanged unchanged ↓*
- **Erythropoietin** would increase, not remain unchanged, to stimulate red blood cell production in response to hypoxia.
- **Oxygen saturation** would decrease, not remain unchanged, at higher altitudes.
Question 5: 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)
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.
Question 6: An academic medical center in the United States is approached by a pharmaceutical company to run a small clinical trial to test the effectiveness of its new drug, compound X. The company wants to know if the measured hemoglobin a1c (Hba1c) of patients with type 2 diabetes receiving metformin and compound X would be lower than that of control subjects receiving only metformin. After a year of study and data analysis, researchers conclude that the control and treatment groups did not differ significantly in their Hba1c levels.
However, parallel clinical trials in several other countries found that compound X led to a significant decrease in Hba1c. Interested in the discrepancy between these findings, the company funded a larger study in the United States, which confirmed that compound X decreased Hba1c levels. After compound X was approved by the FDA, and after several years of use in the general population, outcomes data confirmed that it effectively lowered Hba1c levels and increased overall survival. What term best describes the discrepant findings in the initial clinical trial run by institution A?
A. Type I error
B. Hawthorne effect
C. Type II error (Correct Answer)
D. Publication bias
E. Confirmation bias
Explanation: ***Type II error***
- A **Type II error** occurs when a study fails to **reject a false null hypothesis**, meaning it concludes there is no significant difference or effect when one actually exists.
- In this case, the initial US trial incorrectly concluded that Compound X had no significant effect on HbA1c, while subsequent larger studies and real-world data proved it did.
*Type I error*
- A **Type I error** (alpha error) occurs when a study incorrectly **rejects a true null hypothesis**, concluding there is a significant difference or effect when there isn't.
- This scenario describes the opposite: the initial study failed to find an effect that genuinely existed, indicating a Type II error, not a Type I error.
*Hawthorne effect*
- The **Hawthorne effect** is a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed.
- This effect does not explain the initial trial's failure to detect a real drug effect; rather, it relates to participants changing behavior due to study participation itself.
*Publication bias*
- **Publication bias** occurs when studies with positive or statistically significant results are more likely to be published than those with negative or non-significant results.
- While relevant to the literature as a whole, it doesn't explain the discrepancy in findings within a single drug's development where a real effect was initially missed.
*Confirmation bias*
- **Confirmation bias** is the tendency to search for, interpret, favor, and recall information in a way that confirms one's preexisting beliefs or hypotheses.
- This bias would likely lead researchers to *find* an effect if they expected one, or to disregard data that contradicts their beliefs, which is not what happened in the initial trial.
Question 7: 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)
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**.
Question 8: A research team is working on a new assay meant to increase the sensitivity of testing in cervical cancer. Current sensitivity is listed at 77%. If this research team's latest work culminates in the following results (listed in the table), has the sensitivity improved, and, if so, then by what percentage?
Research team's latest results:
| | Patients with cervical cancer | Patients without cervical cancer |
|--------------------------|-------------------------------|----------------------------------|
| Test is Positive (+) | 47 | 4 |
| Test is Negative (-) | 9 | 44 |
A. No, the research team has seen a decrease in sensitivity according to the new results listed.
B. No, the research team has not seen any improvement in sensitivity according to the new results listed.
C. Yes, the research team has seen an improvement in sensitivity of almost 7% according to the new results listed. (Correct Answer)
D. Yes, the research team has seen an improvement in sensitivity of more than 10% according to the new results listed.
E. Yes, the research team has seen an improvement in sensitivity of less than 2% according to new results listed; this improvement is negligible and should be improved upon for significant contribution to the field.
Explanation: ***Yes, the research team has seen an improvement in sensitivity of almost 7% according to the new results listed.***
- **Sensitivity** is calculated as **True Positives / (True Positives + False Negatives)**. From the table: True Positives = 47, False Negatives = 9.
- New sensitivity = 47 / (47 + 9) = 47 / 56 $\approx$ **83.9%**. Compared to the current sensitivity of 77%, this is an improvement of 83.9% - 77% = **6.9%**, which is almost 7%.
*No, the research team has not seen any improvement in sensitivity according to the new results listed.*
- The new sensitivity calculated is **83.9%**, which is indeed higher than the current sensitivity of **77%**.
- This option incorrectly states there is no improvement, as a clear increase of nearly 7% is observed.
*No, the research team has seen a decrease in sensitivity according to the new results listed.*
- The calculated new sensitivity of **83.9%** is higher than the original 77%, indicating an **increase**, not a decrease.
- This statement is factually incorrect based on the provided data.
*Yes, the research team has seen an improvement in sensitivity of more than 10% according to the new results listed.*
- The improvement is approximately **6.9%** (83.9% - 77%), which is less than 10%.
- This option overstates the degree of improvement observed.
*Yes, the research team has seen an improvement in sensitivity of less than 2% according to new results listed; this improvement is negligible and should be improved upon for significant contribution to the field.*
- The calculated improvement is approximately **6.9%**, not less than 2%.
- While clinical significance can be debated, the mathematical calculation of improvement is not accurately reflected by "less than 2%".
Question 9: Two research groups independently study the same genetic variant's association with diabetes. Study A (n=5,000) reports OR=1.25, 95% CI: 1.05-1.48, p=0.01. Study B (n=50,000) reports OR=1.08, 95% CI: 1.02-1.14, p=0.006. Both studies are methodologically sound. Synthesize these findings to determine the most likely true effect and evaluate implications for clinical and research interpretation.
A. Study B is definitive because of its larger sample size and should replace Study A's findings
B. The study with the lower p-value (Study B) is automatically more reliable
C. The studies are contradictory and no conclusions can be drawn
D. Study A is correct because it was published first
E. The true effect is likely modest (closer to Study B's estimate); Study A likely overestimated due to smaller sample size, but both show statistical significance with clinically marginal effects (Correct Answer)
Explanation: ***The true effect is likely modest (closer to Study B's estimate); Study A likely overestimated due to smaller sample size, but both show statistical significance with clinically marginal effects***
- Study B has significantly higher **statistical power** and **precision** (narrower 95% CI) due to its larger sample size, making its **odds ratio (OR)** estimate more reliable.
- Smaller initial studies often exhibit the **Winner's Curse**, where effect sizes are **overestimated** to reach the threshold for statistical significance.
*Study A is correct because it was published first*
- **Publication order** does not determine the scientific validity or accuracy of genetic association studies.
- Early studies are more prone to **random error** and inflated effect sizes compared to later, larger-scale replications.
*Study B is definitive because of its larger sample size and should replace Study A's findings*
- While Study B is more **precise**, both studies are directionally consistent and both show **statistical significance** (p < 0.05).
- Scientific evidence is **cumulative**; Study B refines and confirms the existence of an association rather than declaring Study A's findings as entirely false.
*The studies are contradictory and no conclusions can be drawn*
- The studies are not contradictory because both **confidence intervals** show an OR > 1.0, and both reach **statistical significance**.
- Both groups found the same **direction of effect**, suggesting a real albeit modest genetic association with diabetes.
*The study with the lower p-value (Study B) is automatically more reliable*
- Reliability depends on **methodological rigor** and **precision**, whereas the p-value is heavily influenced by **sample size**.
- A lower p-value indicates stronger evidence against the **null hypothesis** but does not inherently mean the study is free from bias or more reliable in its effect estimate.
Question 10: A prestigious journal publishes a trial showing a new cancer drug extends survival by 2 months (p=0.001, 95% CI: 1.5-2.5 months). The drug costs $150,000 per patient and causes Grade 3-4 toxicity in 60% of patients. Three prior unpublished trials showed non-significant results (all p>0.20). Synthesize these findings to evaluate the evidence base.
A. This pattern suggests publication bias; the significant result may be a false positive among multiple trials, and the modest benefit must be weighed against substantial toxicity and cost (Correct Answer)
B. The confidence interval proves the drug should be standard of care
C. P-values below 0.01 override concerns about prior negative studies
D. The published study's highly significant p-value validates the drug's efficacy
E. The three unpublished trials are irrelevant to evaluating the published study
Explanation: ***This pattern suggests publication bias; the significant result may be a false positive among multiple trials, and the modest benefit must be weighed against substantial toxicity and cost***
- The existence of three unpublished negative trials alongside one positive one strongly indicates **publication bias** (the file drawer effect), suggesting the positive result might be a **Type I error** or an overestimation.
- **Statistical significance** (p=0.001) does not equal **clinical significance**; a marginal 2-month survival gain must be balanced against extreme **financial cost** and a 60% rate of **Grade 3-4 toxicity**.
*The published study's highly significant p-value validates the drug's efficacy*
- A **low p-value** only indicates that the null hypothesis is unlikely within that specific trial; it does not account for the **context** of other failed experiments.
- Efficacy cannot be validated in isolation when the broader **evidence base** (including unpublished data) shows inconsistent results.
*The three unpublished trials are irrelevant to evaluating the published study*
- All relevant clinical trials must be synthesized via **meta-analysis** or systematic review to determine the true **effect size** of an intervention.
- Ignoring unpublished data leads to **evidence distortion**, where clinicians perceive a drug as more effective than it truly is.
*P-values below 0.01 override concerns about prior negative studies*
- No **p-value** can magically override the **prior probability** of a drug's success; consistent negative results in prior trials increase the likelihood that a later positive result is a **false positive**.
- High-impact medical decisions require a consistent **body of evidence** rather than a single outlier result, regardless of the level of significance.
*The confidence interval proves the drug should be standard of care*
- The **95% Confidence Interval** (1.5–2.5 months) tells us only about the **precision** of the measurement, not the **magnitude of clinical benefit**.
- Becoming a **standard of care** requires a favorable **risk-benefit ratio**, which is undermined here by severe **adverse events** and poor **cost-effectiveness**.
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