Ethics/Biostatistics US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Ethics/Biostatistics. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Ethics/Biostatistics US Medical PG 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
Ethics/Biostatistics 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.
Ethics/Biostatistics US Medical PG Question 2: An investigator for a nationally representative health survey is evaluating the heights and weights of men and women aged 18–74 years in the United States. The investigator finds that for each sex, the distribution of heights is well-fitted by a normal distribution. The distribution of weight is not normally distributed. Results are shown:
Mean Standard deviation
Height (inches), men 69 0.1
Height (inches), women 64 0.1
Weight (pounds), men 182 1.0
Weight (pounds), women 154 1.0
Based on these results, which of the following statements is most likely to be correct?
- A. 86% of heights in women are likely to fall between 63.9 and 64.1 inches.
- B. 99.7% of heights in women are likely to fall between 63.7 and 64.3 inches. (Correct Answer)
- C. 68% of weights in women are likely to fall between 153 and 155 pounds.
- D. 95% of heights in men are likely to fall between 68.85 and 69.15 inches.
- E. 99.7% of heights in men are likely to fall between 68.8 and 69.2 inches.
Ethics/Biostatistics Explanation: ***99.7% of heights in women are likely to fall between 63.7 and 64.3 inches.***
* For a **normal distribution**, approximately 99.7% of values fall within **±3 standard deviations** of the mean.
* For women's height: Mean = 64 inches, Standard Deviation = 0.1 inches. Therefore, 3 SD = 0.3 inches. The range is 64 ± 0.3, which is **63.7 to 64.3 inches**.
*86% of heights in women are likely to fall between 63.9 and 64.1 inches.*
* The range 63.9 to 64.1 inches represents **±1 standard deviation** (64 ± 0.1 inches).
* For a normal distribution, approximately **68%** (not 86%) of values fall within ±1 standard deviation of the mean.
*68% of weights in women are likely to fall between 153 and 155 pounds.*
* While 153 to 155 pounds represents **±1 standard deviation** (154 ± 1 pound), the problem states that the **distribution of weight is not normally distributed**.
* The **68-95-99.7 rule** (empirical rule) only applies to data that follows a normal distribution.
*95% of heights in men are likely to fall between 68.85 and 69.15 inches.*
* For a normal distribution, 95% of values fall within **±2 standard deviations**.
* For men's height: Mean = 69 inches, Standard Deviation = 0.1 inches. Therefore, 2 SD = 0.2 inches. The range for 95% should be 69 ± 0.2, which is **68.8 to 69.2 inches**, not 68.85 to 69.15 inches.
*99.7% of heights in men are likely to fall between 68.8 and 69.2 inches.*
* For a normal distribution, 99.7% of values fall within **±3 standard deviations**.
* For men's height: Mean = 69 inches, Standard Deviation = 0.1 inches. Therefore, 3 SD = 0.3 inches. The range for 99.7% should be 69 ± 0.3, which is **68.7 to 69.3 inches**, not 68.8 to 69.2 inches.
Ethics/Biostatistics US Medical PG Question 3: A clinical trial investigating a new biomedical device used to correct congenital talipes equinovarus (club foot) in infants has recently been published. The study was a preliminary investigation of a new device and as such the sample size is only 20 participants. The results indicate that the new biomedical device is less efficacious than the current standard of care of serial casting (p < 0.001), but the authors mention in the conclusion that it may be due to a single outlier--a patient whose foot remained uncorrected by the conclusion of the study. Which of the following descriptive statistics is the least sensitive to outliers?
- A. Standard deviation
- B. Median (Correct Answer)
- C. Mean
- D. Variance
- E. Mode
Ethics/Biostatistics Explanation: ***Median***
- The **median** is the middle value in a dataset when ordered from least to greatest, making it inherently resistant to extreme values or **outliers**.
- It describes the central tendency without being skewed by a single unusually high or low data point, unlike the mean.
- Among measures of central tendency, the median is the **most robust** to outliers.
*Standard deviation*
- **Standard deviation** measures the spread of data points around the mean, and because it is based on the **mean**, it is highly sensitive to outliers.
- A single outlier can significantly increase the standard deviation, making the data appear more dispersed than it actually is for the majority of observations.
*Mean*
- The **mean** is calculated by summing all values and dividing by the number of values, which makes it directly affected by every data point, especially extreme ones.
- A single **outlier** can pull the mean significantly towards its value, misrepresenting the central tendency of the majority of the data.
*Variance*
- **Variance** is the average of the squared differences from the mean, and like standard deviation, its calculation heavily relies on the **mean**.
- Squaring the differences amplifies the impact of outliers, making variance very sensitive to extreme values.
*Mode*
- The **mode** represents the most frequently occurring value in a dataset and is also resistant to outliers since it only depends on frequency of occurrence.
- However, in small datasets or datasets without repeated values, the mode may be **undefined or uninformative**, making it less useful for describing central tendency compared to the median.
Ethics/Biostatistics US Medical PG Question 4: 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
Ethics/Biostatistics 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.
Ethics/Biostatistics US Medical PG Question 5: A neuro-oncology investigator has recently conducted a randomized controlled trial in which the addition of a novel alkylating agent to radiotherapy was found to prolong survival in comparison to radiotherapy alone (HR = 0.7, p < 0.01). A number of surviving participants who took the alkylating agent reported that they had experienced significant nausea from the medication. The investigator surveyed all participants in both the treatment and the control group on their nausea symptoms by self-report rated mild, moderate, or severe. The investigator subsequently compared the two treatment groups with regards to nausea level.
| | Mild nausea | Moderate nausea | Severe nausea |
|---|---|---|---|
| Treatment group (%) | 20 | 30 | 50 |
| Control group (%) | 35 | 35 | 30 |
Which of the following statistical methods would be most appropriate to assess the statistical significance of these results?
- A. Chi-square test (Correct Answer)
- B. Pearson correlation coefficient
- C. Multiple logistic regression
- D. Unpaired t-test
- E. Paired t-test
Ethics/Biostatistics Explanation: **Chi-square test**
- The **Chi-square test** is appropriate for comparing **categorical data** (mild, moderate, severe) between two or more independent groups (treatment vs. control).
- It assesses whether there is a statistically significant association between the two categorical variables (treatment group and nausea severity).
*Pearson correlation coefficient*
- The **Pearson correlation coefficient** is used to measure the **linear relationship** between two **continuous variables**.
- Nausea severity (mild, moderate, severe) is an **ordinal categorical variable**, not a continuous one.
*Multiple logistic regression*
- **Multiple logistic regression** is used to predict a **binary outcome** (e.g., presence or absence of nausea) based on one or more independent variables, which can be continuous or categorical.
- The outcome here is **ordinal categorical** (mild, moderate, severe nausea), not binary. While logistic regression can be adapted for ordinal outcomes, a simpler Chi-square test is more direct for comparing distributions without prediction.
*Unpaired t-test*
- An **unpaired t-test** is used to compare the **means of two independent continuous variables**.
- Nausea levels are categorical, and we are interested in comparing proportions within categories, not means.
*Paired t-test*
- A **paired t-test** is used to compare the **means of two related (paired) continuous variables**.
- The study involves independent treatment and control groups, and the nausea data is categorical, making the paired t-test unsuitable.
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