Multi-center studies — MCQs

10 questions

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 surgeon is interested in studying how different surgical techniques impact the healing of tendon injuries. In particular, he will compare 3 different types of suture repairs biomechanically in order to determine the maximum load before failure of the tendon 2 weeks after repair. He collects data on maximum load for 90 different repaired tendons from an animal model. Thirty tendons were repaired using each of the different suture techniques. Which of the following statistical measures is most appropriate for analyzing the results of this study?

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?

An epidemiologist is evaluating the efficacy of Noxbinle in preventing HCC deaths at the population level. A clinical trial shows that over 5 years, the mortality rate from HCC was 25% in the control group and 15% in patients treated with Noxbinle 100 mg daily. Based on this data, how many patients need to be treated with Noxbinle 100 mg to prevent, on average, one death from HCC?

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?

You are currently employed as a clinical researcher working on clinical trials of a new drug to be used for the treatment of Parkinson's disease. Currently, you have already determined the safe clinical dose of the drug in a healthy patient. You are in the phase of drug development where the drug is studied in patients with the target disease to determine its efficacy. Which of the following phases is this new drug currently in?

In 2013 the national mean score on the USMLE Step 1 exam was 227 with a standard deviation of 22. Assuming that the scores for 15,000 people follow a normal distribution, approximately how many students scored above the mean but below 250?

A statistician wants to study the effects of a medicine in three groups-humans, animals, and plants. He then selects randomly from these three groups. Which type of sampling is being performed?

A study was undertaken to establish the relationship between the consumption of a vegetarian or non-vegetarian diet and the presence of diseases. Which statistical test should be used?

Q10

A group of 80 people is being studied to determine the effect of diet modification on cholesterol levels. To compare the mean cholesterol levels before and after the diet modification in this group, which statistical test should be used?

Multi-center studies US Medical PG Practice Questions and MCQs

Question 1: 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

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.

Question 2: A surgeon is interested in studying how different surgical techniques impact the healing of tendon injuries. In particular, he will compare 3 different types of suture repairs biomechanically in order to determine the maximum load before failure of the tendon 2 weeks after repair. He collects data on maximum load for 90 different repaired tendons from an animal model. Thirty tendons were repaired using each of the different suture techniques. Which of the following statistical measures is most appropriate for analyzing the results of this study?

A. Chi-squared
B. Wilcoxon rank sum
C. Pearson r coefficient
D. Student t-test
E. ANOVA (Correct Answer)

Explanation: ***ANOVA*** - **ANOVA (Analysis of Variance)** is appropriate here because it compares the means of **three or more independent groups** (the three different suture techniques) on a continuous dependent variable (maximum load before failure). - The study has three distinct repair techniques, each with 30 tendons, making ANOVA suitable for determining if there are statistically significant differences among their mean failure loads. *Chi-squared* - The **Chi-squared test** is used for analyzing **categorical data** (frequencies or proportions) to determine if there is an association between two nominal variables. - This study involves quantitative measurement (maximum load), not categorical data, making Chi-squared inappropriate. *Wilcoxon rank sum* - The **Wilcoxon rank sum test** (also known as Mann-Whitney U test) is a **non-parametric test** used to compare two independent groups when the data is not normally distributed or is ordinal. - While the study has independent groups, it involves three groups, and the dependent variable is continuous, making ANOVA a more powerful and appropriate choice assuming normal distribution. *Pearson r coefficient* - The **Pearson r coefficient** measures the **strength and direction of a linear relationship between two continuous variables**. - This study aims to compare means across different groups, not to determine the correlation between two continuous variables. *Student t-test* - The **Student t-test** is used to compare the means of **exactly two groups** (either independent or paired) on a continuous dependent variable. - This study involves comparing three different suture techniques, not just two, making the t-test unsuitable.

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: An epidemiologist is evaluating the efficacy of Noxbinle in preventing HCC deaths at the population level. A clinical trial shows that over 5 years, the mortality rate from HCC was 25% in the control group and 15% in patients treated with Noxbinle 100 mg daily. Based on this data, how many patients need to be treated with Noxbinle 100 mg to prevent, on average, one death from HCC?

A. 20
B. 73
C. 10 (Correct Answer)
D. 50
E. 100

Explanation: ***10*** - The **number needed to treat (NNT)** is calculated by first finding the **absolute risk reduction (ARR)**. - **ARR** = Risk in control group - Risk in treatment group = 25% - 15% = **10%** (or 0.10). - **NNT = 1 / ARR** = 1 / 0.10 = **10 patients**. - This means that **10 patients must be treated with Noxbinle to prevent one death from HCC** over 5 years. *20* - This would result from an ARR of 5% (1/0.05 = 20), which is not supported by the data. - May arise from miscalculating the risk difference or incorrectly halving the actual ARR. *73* - This value does not correspond to any standard calculation of NNT from the given mortality rates. - May result from confusion with other epidemiological measures or calculation error. *50* - This would correspond to an ARR of 2% (1/0.02 = 50), which significantly underestimates the actual risk reduction. - Could result from incorrectly calculating the difference as a proportion rather than absolute percentage points. *100* - This would correspond to an ARR of 1% (1/0.01 = 100), grossly underestimating the treatment benefit. - May result from confusing ARR with relative risk reduction or other calculation errors.

Question 5: 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 6: You are currently employed as a clinical researcher working on clinical trials of a new drug to be used for the treatment of Parkinson's disease. Currently, you have already determined the safe clinical dose of the drug in a healthy patient. You are in the phase of drug development where the drug is studied in patients with the target disease to determine its efficacy. Which of the following phases is this new drug currently in?

A. Phase 4
B. Phase 1
C. Phase 2 (Correct Answer)
D. Phase 0
E. Phase 3

Explanation: ***Phase 2*** - **Phase 2 trials** involve studying the drug in patients with the target disease to assess its **efficacy** and further evaluate safety, typically involving a few hundred patients. - The question describes a stage after safe dosing in healthy patients (Phase 1) and before large-scale efficacy confirmation (Phase 3), focusing on efficacy in the target population. *Phase 4* - **Phase 4 trials** occur **after a drug has been approved** and marketed, monitoring long-term effects, optimal use, and rare side effects in a diverse patient population. - This phase is conducted post-market approval, whereas the question describes a drug still in development prior to approval. *Phase 1* - **Phase 1 trials** primarily focus on determining the **safety and dosage** of a new drug in a **small group of healthy volunteers** (or sometimes patients with advanced disease if the drug is highly toxic). - The question states that the safe clinical dose in a healthy patient has already been determined, indicating that Phase 1 has been completed. *Phase 0* - **Phase 0 trials** are exploratory, very early-stage studies designed to confirm that the drug reaches the target and acts as intended, typically involving a very small number of doses and participants. - These trials are conducted much earlier in the development process, preceding the determination of safe clinical doses and large-scale efficacy studies. *Phase 3* - **Phase 3 trials** are large-scale studies involving hundreds to thousands of patients to confirm **efficacy**, monitor side effects, compare it to commonly used treatments, and collect information that will allow the drug to be used safely. - While Phase 3 does assess efficacy, it follows Phase 2 and is typically conducted on a much larger scale before submitting for regulatory approval.

Question 7: In 2013 the national mean score on the USMLE Step 1 exam was 227 with a standard deviation of 22. Assuming that the scores for 15,000 people follow a normal distribution, approximately how many students scored above the mean but below 250?

A. 5,100 (Correct Answer)
B. 4,500
C. 6,000
D. 3,750
E. 6,750

Explanation: ***5,100*** - To solve this, first calculate the **z-score** for 250: (250 - 227) / 22 = 1.045. - Using a **z-table**, the area under the curve from the mean (z=0) to z=1.045 is approximately 0.353. Multiplying this by 15,000 students gives approximately **5,295 students**, which is closest to 5,100. *4,500* - This answer would imply a smaller proportion of students between the mean and 250 (around 30%), which is lower than the calculated z-score of 1.045 suggests. - It does not accurately reflect the area under the **normal distribution curve** for the given range. *6,000* - This option would mean that approximately 40% of students scored in this range, which would correspond to a z-score much higher than 1.045 or a different standard deviation. - This calculation overestimates the number of students within the specified range. *3,750* - This value represents 25% of the total students (15,000 * 0.25), indicating that only a quarter of the distribution lies in this range. - This significantly underestimates the proportion of students scoring between the mean and 250 for the given standard deviation. *6,750* - This option reflects approximately 45% of the total student population (15,000 * 0.45), which would correspond to a much larger z-score or a different distribution. - This value is an overestimation and does not align with the standard normal distribution probabilities for the given parameters.

Question 8: A statistician wants to study the effects of a medicine in three groups-humans, animals, and plants. He then selects randomly from these three groups. Which type of sampling is being performed?

A. Simple random sampling
B. Systematic sampling
C. Stratified random sampling (Correct Answer)
D. Cluster sampling
E. Convenience sampling

Explanation: ***Stratified random sampling*** - This method involves dividing the population into **distinct subgroups (strata)** based on shared characteristics (in this case, humans, animals, and plants), and then performing a simple random sample within each stratum. - This ensures that all subgroups are proportionally represented in the sample, which is appropriate when studying effects across different biological categories. *Simple random sampling* - This method involves selecting individuals from the entire population **purely by chance**, without first dividing them into subgroups. - It would not guarantee representation from all three distinct groups (humans, animals, and plants), which is essential for studying differential effects. *Systematic sampling* - This involves selecting samples at **regular intervals** from an ordered list or sequence. - This method is not suitable here because the population is divided into distinct, non-ordered groups rather than a continuous sequence. *Cluster sampling* - This method involves dividing the population into **clusters**, then randomly selecting some clusters and sampling all individuals within those selected clusters. - In this scenario, the initial groups (humans, animals, plants) are strata, not clusters, as the intent is to sample from within each group, not to treat the groups themselves as primary sampling units. *Convenience sampling* - This is a **non-probability sampling method** where subjects are selected based on ease of access rather than random selection. - The question explicitly states that random selection is performed from each group, ruling out convenience sampling.

Question 9: A study was undertaken to establish the relationship between the consumption of a vegetarian or non-vegetarian diet and the presence of diseases. Which statistical test should be used?

A. Chi-square test (Correct Answer)
B. T-test
C. ANOVA
D. Fisher's exact test
E. Mann-Whitney U test

Explanation: ***Chi-square test*** - The **chi-square test** is appropriate when analyzing the relationship between two **categorical variables**. In this scenario, "diet type" (vegetarian/non-vegetarian) and "presence of disease" (yes/no) are both categorical variables. - This test determines if there is a statistically significant association between the frequency counts of these two variables in a contingency table. *T-test* - A **t-test** is used to compare the **means** of two groups, typically when the dependent variable is continuous. - This test is unsuitable here because the presence of disease and diet type are categorical, not continuous, variables. *ANOVA* - **ANOVA** (Analysis of Variance) is used to compare the **means** of three or more groups, often with a continuous dependent variable. - Similar to the t-test, ANOVA is not applicable as the study involves categorical variables, not the comparison of means across multiple groups. *Fisher's exact test* - **Fisher's exact test** is similar to the chi-square test but specifically used for **small sample sizes** where the expected frequencies in any cell of the contingency table are less than 5. - While it analyzes categorical data, the chi-square test is the more general and commonly preferred test for larger sample sizes, which is generally assumed unless otherwise specified. *Mann-Whitney U test* - The **Mann-Whitney U test** is a non-parametric test used to compare differences between two independent groups when the dependent variable is **ordinal or continuous** but not normally distributed. - This test is not appropriate for analyzing the association between two categorical variables, as it requires at least one variable to have ranked or continuous data.

Question 10: A group of 80 people is being studied to determine the effect of diet modification on cholesterol levels. To compare the mean cholesterol levels before and after the diet modification in this group, which statistical test should be used?

A. Paired t-test (Correct Answer)
B. McNemar test
C. Chi-square test
D. Wilcoxon signed-rank test
E. Independent t-test

Explanation: ***Paired t-test*** - A **paired t-test** is appropriate for comparing means from two related samples, such as "before" and "after" measurements on the **same individuals**. - It assesses whether there is a statistically significant difference between these **dependent observations**. *Independent t-test* - The independent t-test compares means between **two separate groups** (unrelated samples). - It is inappropriate here because we have **paired data** from the same individuals measured twice, not two independent groups. *McNemar test* - The McNemar test is used for comparing **paired nominal data**, typically in a 2×2 table, for example, before-after changes in a proportion or categorical outcome. - It is not suitable for **continuous data** like cholesterol levels. *Chi-square test* - The chi-square test is used to assess the association between **two categorical variables** or to compare observed frequencies with expected frequencies. - It is not designed for comparing means of **continuous variables** in paired samples. *Wilcoxon signed-rank test* - The Wilcoxon signed-rank test is a **non-parametric alternative to the paired t-test**, used when the data are not normally distributed or when the sample size is small. - While it's used for paired data, the paired t-test is generally preferred when parametric assumptions (like **normality**) can be met, especially with a sample size of 80.

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