Cox proportional hazards model US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Cox proportional hazards model. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Cox proportional hazards model US Medical PG Question 1: Recently, clarithromycin was found to have an increased risk of cardiac death in a Danish study. This study analyzed patients who were previously treated with clarithromycin or another antibiotic, and then they were followed over time to ascertain if cardiac death resulted. What type of study design does this represent?
- A. Cross-sectional study
- B. Randomized controlled trial
- C. Case control study
- D. Cohort study (Correct Answer)
Cox proportional hazards model Explanation: ***Cohort study***
- This study design involves following a group of individuals (a **cohort**) over time to observe the incidence of specific outcomes, in this case, **cardiac death**.
- The study identifies groups based on exposure (clarithromycin treatment vs. another antibiotic) and then tracks them for future events, which is characteristic of a **prospective cohort study**.
*Cross-sectional study*
- A **cross-sectional study** assesses exposure and outcome at a **single point in time**.
- It does not involve following individuals over time, making it unsuitable for studying the temporal relationship between antibiotic use and subsequent cardiac death.
*Randomized controlled trial*
- A **randomized controlled trial (RCT)** involves randomly assigning participants to an intervention or control group to determine the effect of the intervention.
- This study did not involve random assignment of clarithromycin but rather observed groups based on **prior treatment**, ruling out an RCT.
*Case control study*
- A **case-control study** starts with individuals who have the outcome (cases) and individuals who do not (controls) and then retrospectively looks back at their exposures.
- This study started with exposed individuals (treated with clarithromycin) and then followed them forward, which is the opposite direction of a case-control study.
Cox proportional hazards model US Medical PG Question 2: Group of 100 medical students took an end of the year exam. The mean score on the exam was 70%, with a standard deviation of 25%. The professor states that a student's score must be within the 95% confidence interval of the mean to pass the exam. Which of the following is the minimum score a student can have to pass the exam?
- A. 45%
- B. 63.75%
- C. 67.5%
- D. 20%
- E. 65% (Correct Answer)
Cox proportional hazards model Explanation: ***65%***
- To find the **95% confidence interval (CI) of the mean**, we use the formula: Mean ± (Z-score × Standard Error). For a 95% CI, the Z-score is approximately **1.96**.
- The **Standard Error (SE)** is calculated as SD/√n, where n is the sample size (100 students). So, SE = 25%/√100 = 25%/10 = **2.5%**.
- The 95% CI is 70% ± (1.96 × 2.5%) = 70% ± 4.9%. The lower bound is 70% - 4.9% = **65.1%**, which rounds to **65%** as the minimum passing score.
*45%*
- This value is significantly lower than the calculated lower bound of the 95% confidence interval (approximately 65.1%).
- It would represent a score far outside the defined passing range.
*63.75%*
- This value falls below the calculated lower bound of the 95% confidence interval (approximately 65.1%).
- While close, this score would not meet the professor's criterion for passing.
*67.5%*
- This value is within the 95% confidence interval (65.1% to 74.9%) but is **not the minimum score**.
- Lower scores within the interval would still qualify as passing.
*20%*
- This score is extremely low and falls significantly outside the 95% confidence interval for a mean of 70%.
- It would indicate performance far below the defined passing threshold.
Cox proportional hazards model US Medical PG 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)
Cox proportional hazards model 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.
Cox proportional hazards model US Medical PG Question 4: Which of the following study designs would be most appropriate to investigate the association between electronic cigarette use and the subsequent development of lung cancer?
- A. Subjects with lung cancer who smoke and subjects with lung cancer who did not smoke
- B. Subjects who smoke electronic cigarettes and subjects who smoke normal cigarettes
- C. Subjects with lung cancer who smoke and subjects without lung cancer who smoke
- D. Subjects with lung cancer and subjects without lung cancer
- E. Subjects who smoke electronic cigarettes and subjects who do not smoke (Correct Answer)
Cox proportional hazards model Explanation: ***Subjects who smoke electronic cigarettes and subjects who do not smoke***
- This design represents a **cohort study**, which is ideal for investigating the **incidence** of a disease (lung cancer) in groups exposed and unexposed to a risk factor (electronic cigarette use).
- By following these two groups over time, researchers can directly compare the **risk of developing lung cancer** in e-cigarette users versus non-smokers.
*Subjects with lung cancer who smoke and subjects with lung cancer who did not smoke*
- This option incorrectly compares two groups both with lung cancer, where the exposure to smoking can either be **electronic or traditional cigarettes,** but does not provide a control group without lung cancer to assess the association.
- This design would not allow for the calculation of an **incidence rate** or a **relative risk** of lung cancer development specific to electronic cigarette use.
*Subjects who smoke electronic cigarettes and subjects who smoke normal cigarettes*
- This design compares two different types of smoking, which might be useful for comparing their relative risks but doesn't include a **non-smoking control group** to establish the absolute association with electronic cigarettes.
- While it could show if e-cigarettes are "safer" than traditional cigarettes, it wouldn't directly answer whether e-cigarettes themselves **cause lung cancer**.
*Subjects with lung cancer who smoke and subjects without lung cancer who smoke*
- This describes a **case-control study** but focuses on smoking in general rather than specifically electronic cigarettes, which is the independent variable of interest.
- While valuable for identifying risk factors, it would need to specifically differentiate between **electronic cigarette smokers** and other smokers to answer the question adequately.
*Subjects with lung cancer and subjects without lung cancer*
- This general description of a **case-control study** is too broad; it does not specify the exposure of interest, which is electronic cigarette use.
- To be relevant, the study would need to gather data on **electronic cigarette use** in both the lung cancer group and the non-lung cancer control group.
Cox proportional hazards model US Medical PG Question 5: A biostatistician is processing data for a large clinical trial she is working on. The study is analyzing the use of a novel pharmaceutical compound for the treatment of anorexia after chemotherapy with the outcome of interest being the change in weight while taking the drug. While most participants remained about the same weight or continued to lose weight while on chemotherapy, there were smaller groups of individuals who responded very positively to the orexic agent. As a result, the data had a strong positive skew. The biostatistician wishes to report the measures of central tendency for this project. Just by understanding the skew in the data, which of the following can be expected for this data set?
- A. Mean = median = mode
- B. Mean < median < mode
- C. Mean > median > mode (Correct Answer)
- D. Mean > median = mode
- E. Mean < median = mode
Cox proportional hazards model Explanation: ***Mean > median > mode***
- In a dataset with a **strong positive skew**, the tail of the distribution is on the right, pulled by a few **unusually large values**.
- These extreme high values disproportionately influence the **mean**, pulling it to the right (higher value), while the **median** (middle value) is less affected, and the **mode** (most frequent value) is often located at the peak of the distribution towards the left.
*Mean = median = mode*
- This relationship between the measures of central tendency is characteristic of a **perfectly symmetrical distribution**, such as a **normal distribution**, where there is no skew.
- In a symmetrical distribution, the mean, median, and mode are all located at the exact center of the data.
*Mean < median < mode*
- This order is typical for a dataset with a **negative skew**, where the tail is on the left due to a few **unusually small values**.
- In a negatively skewed distribution, the mean is pulled to the left (lower value) by the small values, making it less than the median and mode.
*Mean > median = mode*
- This configuration is generally not characteristic of standard skewed distributions and would imply a specific, less common bimodal or complex distribution shape where the mode coincides with the median, but the mean is pulled higher.
- While theoretically possible, it doesn't describe a typical positively skewed distribution where the mode is usually the lowest of the three.
*Mean < median = mode*
- This relationship would suggest a negatively skewed distribution where the median and mode are equal, but the mean is pulled to the left (lower value) by a leftward tail.
- Again, this is a less typical representation of a standard negatively skewed distribution, which often follows the Mean < Median < Mode pattern.
Cox proportional hazards model US Medical PG Question 6: A 47-year-old man comes to the physician for a routine health maintenance examination. He has no complaints and has no history of serious illness. He works as a forklift operator in a factory. His brother died of malignant melanoma. He smokes occasionally and drinks a glass of wine once a week. His pulse is 79/min and blood pressure is 129/84 mm Hg. Which of the following causes of death is this patient most at risk for over the next 15 years?
- A. Industrial accident
- B. Coronary artery disease (Correct Answer)
- C. Prostate cancer
- D. Malignant melanoma
- E. Lung cancer
Cox proportional hazards model Explanation: ***Coronary artery disease***
- **Coronary artery disease (CAD)** is the **leading cause of death** in middle-aged men in the United States, making it the statistically most likely cause of death for this patient over the next 15 years.
- This patient has multiple modifiable risk factors including male sex, smoking (even occasional), and blood pressure of 129/84 mm Hg (elevated blood pressure/stage 1 hypertension by current guidelines).
- Even with relatively modest risk factors, the cumulative 15-year risk of cardiovascular mortality substantially exceeds other causes of death in this demographic group.
*Industrial accident*
- While working as a forklift operator carries some occupational risk, **industrial accidents** account for a very small proportion of deaths compared to chronic diseases in this age group.
- There is no indication of high-risk working conditions or safety concerns that would elevate this above cardiovascular disease as a cause of death.
*Prostate cancer*
- At age 47, the patient is relatively young for **prostate cancer** mortality. Most prostate cancer deaths occur in men over 65.
- While prostate cancer is common in older men, it typically has a long natural history, and mortality within 15 years would be less likely than cardiovascular disease in this age group.
- No specific high-risk features (family history, African-American ethnicity) are mentioned.
*Malignant melanoma*
- Although his brother died of **malignant melanoma**, family history alone does not make this the most likely cause of death over cardiovascular disease.
- The patient has no described personal risk factors (numerous nevi, history of severe sunburns, fair skin) or current lesions of concern.
- Melanoma mortality rates are substantially lower than cardiovascular disease mortality in middle-aged men.
*Lung cancer*
- The patient smokes **occasionally**, which confers some increased risk, but this is not described as heavy or chronic smoking.
- **Lung cancer** typically requires more substantial cumulative tobacco exposure (pack-years) to become a leading cause of mortality.
- Even in smokers, cardiovascular disease often causes death before lung cancer in this age group, particularly with modest smoking history.
Cox proportional hazards model US Medical PG Question 7: A survey was conducted in a US midwestern town in an effort to assess maternal mortality over the past year. The data from the survey are given in the table below:
Women of childbearing age 250,000
Maternal deaths 2,500
Number of live births 100, 000
Number of deaths of women of childbearing age 7,500
Maternal death is defined as the death of a woman while pregnant or within 42 days of termination of pregnancy from any cause related to or aggravated by, the pregnancy. Which of the following is the maternal mortality rate in this midwestern town?
- A. 1,000 per 100,000 live births
- B. 33 per 100,000 live births
- C. 3,000 per 100,000 live births
- D. 33,300 per 100,000 live births
- E. 2,500 per 100,000 live births (Correct Answer)
Cox proportional hazards model Explanation: ***2,500 per 100,000 live births***
- The maternal mortality rate is calculated as the number of **maternal deaths** per 100,000 **live births**. The given data directly provide these values.
- Calculation: (2,500 maternal deaths / 100,000 live births) × 100,000 = **2,500 per 100,000 live births**.
*1,000 per 100,000 live births*
- This value is incorrect as it does not align with the provided numbers for maternal deaths and live births in the calculation.
- It might result from a miscalculation or using incorrect numerator/denominator values from the dataset.
*33 per 100,000 live births*
- This value is significantly lower than the correct rate and suggests a substantial error in calculation or an incorrect understanding of how the maternal mortality rate is derived.
- It could potentially result from dividing the number of live births by maternal deaths, which is the inverse of the correct formula.
*3,000 per 100,000 live births*
- This option is close to the correct answer but slightly higher, indicating a possible calculation error, for instance, including non-maternal deaths or other causes of deaths in the numerator.
- The definition of maternal death is specific to pregnancy-related or aggravated causes, so extraneous deaths would inflate the rate.
*33,300 per 100,000 live births*
- This figure results from incorrectly calculating the proportion of maternal deaths among all deaths of women of childbearing age: (2,500 / 7,500) × 100,000 = 33,333.
- This is a conceptual error as the maternal mortality rate should use live births as the denominator, not total deaths of women of childbearing age.
Cox proportional hazards model US Medical PG Question 8: 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
Cox proportional hazards model 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.
Cox proportional hazards model US Medical PG Question 9: The mean, median, and mode weight of 37 newborns in a hospital nursery is 7 lbs 2 oz. In fact, there are 7 infants in the nursery that weigh exactly 7 lbs 2 oz. The standard deviation of the weights is 2 oz. The weights follow a normal distribution. A newborn delivered at 10 lbs 2 oz is added to the data set. What is most likely to happen to the mean, median, and mode with the addition of this new data point?
- A. The mean will increase; the median will increase; the mode will stay the same
- B. The mean will increase; the median will stay the same; the mode will stay the same (Correct Answer)
- C. The mean will stay the same; the median will increase; the mode will stay the same
- D. The mean will increase; the median will increase; the mode will increase
- E. The mean will stay the same; the median will increase; the mode will increase
Cox proportional hazards model Explanation: ***The mean will increase; the median will stay the same; the mode will stay the same***
- The **mean** is highly sensitive to outliers. Adding a newborn weighing 10 lbs 2 oz (significantly heavier than the original mean of 7 lbs 2 oz) will increase the total sum of weights, thus **increasing the mean**.
- The **median** is the middle value in an ordered dataset. With 37 newborns, the median is the 19th value. Adding one more (38 total) makes the median the average of the 19th and 20th values. Since the new value (10 lbs 2 oz) is added at the extreme high end of the distribution, the 19th and 20th positions contain the same values as before. Therefore, the median will **stay the same**.
- The **mode** is the most frequent value. Since there are 7 infants already at 7 lbs 2 oz, adding a single infant at 10 lbs 2 oz will not change the most frequent weight in the dataset. The mode will **stay the same** at 7 lbs 2 oz.
*The mean will increase; the median will increase; the mode will stay the same*
- While the **mean will increase** due to the added outlier, the **median will not change**. With 38 observations, the median becomes the average of the 19th and 20th values, which remain unchanged since the outlier is added at position 38.
- The **mode** correctly stays at 7 lbs 2 oz as the new data point does not become the most frequent value.
*The mean will stay the same; the median will increase; the mode will stay the same*
- The **mean will not stay the same** because an outlier significantly higher than the current mean will always pull the mean higher.
- The **median will also not increase** as the middle values (19th and 20th positions) remain unchanged when adding an extreme outlier.
*The mean will increase; the median will increase; the mode will increase*
- While the **mean will increase**, the **median will not change** because the middle positions are unaffected by adding one extreme outlier.
- The **mode will not change** as the new data point (10 lbs 2 oz) is unique and doesn't become the most frequent value; 7 lbs 2 oz remains most frequent with 7 occurrences.
*The mean will stay the same; the median will increase; the mode will increase*
- This option is incorrect because the **mean will definitely increase** with the addition of a much larger value.
- The **median will not increase** as it depends on the middle positions, not extreme values.
- The **mode will not increase** as adding one 10 lb 2 oz infant won't make that weight the most frequent.
Cox proportional hazards model US Medical PG Question 10: Many large clinics have noticed that the prevalence of primary biliary cholangitis (PBC) has increased significantly over the past 20 years. An epidemiologist is working to identify possible reasons for this. After analyzing a series of nationwide health surveillance databases, the epidemiologist finds that the incidence of PBC has remained stable over the past 20 years. Which of the following is the most plausible explanation for the increased prevalence of PBC?
- A. Improved quality of care for PBC (Correct Answer)
- B. Increased availability of diagnostic testing for PBC
- C. Increased exposure to environmental risk factors for PBC
- D. Increased awareness of PBC among clinicians
- E. Increased average age of the population at risk for PBC
Cox proportional hazards model Explanation: ***Improved quality of care for PBC***
- This leads to a **longer survival time** for patients with PBC. When incidence remains stable but patients live longer, the cumulative number of living cases (prevalence) naturally increases.
- An increase in prevalence with stable incidence is a classic indicator of **improved patient survival** due to better management or treatment.
*Increased availability of diagnostic testing for PBC*
- This would primarily impact the **incidence** of PBC by detecting more cases that were previously undiagnosed. The question states that the incidence has remained stable.
- While improved diagnostics might initially increase *reported* incidence, if the true incidence is stable, it wouldn't explain a sustained rise in prevalence without a corresponding change in incidence or survival.
*Increased exposure to environmental risk factors for PBC*
- This would directly lead to an **increase in the incidence** of PBC, as more people would be developing the disease.
- Since the incidence is stable, an increase in environmental risk factors is not the most plausible explanation for increased prevalence.
*Increased awareness of PBC among clinicians*
- Similar to increased diagnostic testing, increased awareness would likely lead to the diagnosis of more new cases, thus **increasing the incidence** of PBC.
- A stable incidence despite increased awareness means that the actual rate of new cases developing the disease has not changed, ruling this out as the primary cause of increased prevalence.
*Increased average age of the population at risk for PBC*
- An aging population could potentially increase the incidence of age-related diseases. However, if the **incidence has remained stable**, it implies that even with an older population, the rate of new diagnoses has not increased.
- While age is a risk factor for PBC, an increase in prevalence without a change in incidence suggests a factor influencing the duration of the disease rather than its onset.
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