Time-to-event analysis US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Time-to-event analysis. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Time-to-event analysis US Medical PG Question 1: A researcher is trying to determine whether a newly discovered substance X can be useful in promoting wound healing after surgery. She conducts this study by enrolling the next 100 patients that will be undergoing this surgery and separating them into 2 groups. She decides which patient will be in which group by using a random number generator. Subsequently, she prepares 1 set of syringes with the novel substance X and 1 set of syringes with a saline control. Both of these sets of syringes are unlabeled and the substances inside cannot be distinguished. She gives the surgeon performing the surgery 1 of the syringes and does not inform him nor the patient which syringe was used. After the study is complete, she analyzes all the data that was collected and performs statistical analysis. This study most likely provides which level of evidence for use of substance X?
- A. Level 3
- B. Level 1 (Correct Answer)
- C. Level 4
- D. Level 5
- E. Level 2
Time-to-event analysis Explanation: ***Level 1***
- The study design described is a **randomized controlled trial (RCT)**, which is considered the **highest level of evidence (Level 1)** in the hierarchy of medical evidence.
- Key features like **randomization**, **control group**, and **blinding (double-blind)** help minimize bias and strengthen the validity of the findings.
*Level 2*
- Level 2 evidence typically comprises **well-designed controlled trials without randomization** (non-randomized controlled trials) or **high-quality cohort studies**.
- While strong, they do not possess the same level of internal validity as randomized controlled trials.
*Level 3*
- Level 3 evidence typically includes **case-control studies** or **cohort studies**, which are observational designs and carry a higher risk of bias compared to RCTs.
- These studies generally do not involve randomization or intervention assignment by the researchers.
*Level 4*
- Level 4 evidence is usually derived from **case series** or **poor quality cohort and case-control studies**.
- These studies provide descriptive information or investigate associations without strong control for confounding factors.
*Level 5*
- Level 5 evidence is the **lowest level of evidence**, consisting of **expert opinion** or **animal research/bench research**.
- This level lacks human clinical data or systematic investigative rigor needed for higher evidence levels.
Time-to-event analysis US Medical PG Question 2: 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)
Time-to-event analysis 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.
Time-to-event analysis US Medical PG Question 3: A resident in the department of obstetrics and gynecology is reading about a randomized clinical trial from the late 1990s that was conducted to compare breast cancer mortality risk, disease localization, and tumor size in women who were randomized to groups receiving either annual mammograms starting at age 40 or annual mammograms starting at age 50. One of the tables in the study compares the two experimental groups with regard to socioeconomic demographics (e.g., age, income), medical conditions at the time of recruitment, and family history of breast cancer. The purpose of this table is most likely to evaluate which of the following?
- A. Observer bias
- B. Statistical power
- C. Confounding
- D. Randomization (Correct Answer)
- E. Effect modification
Time-to-event analysis Explanation: ***Randomization***
- In a randomized clinical trial, the purpose of comparing baseline characteristics between experimental groups is to assess if **randomization successfully distributed potential confounders** evenly.
- An even distribution of baseline characteristics suggests that any observed differences in outcomes are more likely due to the intervention rather than **pre-existing differences** between the groups.
*Observer bias*
- **Observer bias** occurs when researchers' expectations influence their observations or interpretation of results, which is not evaluated by comparing baseline demographics.
- This type of bias is typically mitigated through **blinding** of researchers or participants, rather than checking baseline characteristics.
*Statistical power*
- **Statistical power** refers to the probability of correctly rejecting a false null hypothesis and detecting a true effect.
- It is determined by factors like sample size and effect size, not by the **balance of baseline characteristics** between groups.
*Effect modification*
- **Effect modification** occurs when the effect of an exposure on an outcome varies across different levels of a third variable.
- This is an **analytical consideration** explored in later stages of data analysis, not a concern addressed by comparing baseline characteristics.
*Confounding*
- **Confounding** occurs when an extraneous variable is associated with both the exposure and the outcome, distorting the true relationship.
- While the baseline table helps verify that potential confounders are evenly distributed, the primary purpose is to evaluate whether **randomization was successful**, not to directly assess confounding as an analysis concern.
Time-to-event analysis US Medical PG Question 4: A 17-year-old man is brought by his mother to his pediatrician in order to complete medical clearance forms prior to attending college. During the visit, his mother asks about what health risks he should be aware of in college. Specifically, she recently saw on the news that some college students were killed by a fatal car crash. She therefore asks about causes of death in this population. Which of the following is true about the causes of death in college age individuals?
- A. More of them die from homicide than suicide
- B. More of them die from suicide than injuries
- C. More of them die from cancer than suicide
- D. More of them die from homicide than injuries
- E. More of them die from homicide than cancer (Correct Answer)
Time-to-event analysis Explanation: ***More of them die from homicide than cancer***
- While relatively rare, **homicide rates** for college-aged individuals (18-24 years) are generally higher than their rates of death due to **cancer**.
- **Cancer** is a leading cause of death in older populations but is much less common in young adults.
*More of them die from homicide than suicide*
- **Suicide** is a significantly more common cause of death than homicide among college-aged individuals.
- Data consistently shows that **suicide** ranks as one of the top causes of death in this demographic, often second only to unintentional injuries.
*More of them die from suicide than injuries*
- **Unintentional injuries** (including motor vehicle accidents, accidental poisoning, and falls) are the leading cause of death in the 18-24 age group.
- **Suicide** is typically the second leading cause, meaning more individuals die from injuries than from suicide.
*More of them die from cancer than suicide*
- As mentioned, **suicide** is a much more prevalent cause of death in young adults than cancer.
- **Cancer deaths** are relatively uncommon in this age group compared to other causes like injuries and suicide.
*More of them die from homicide than injuries*
- **Unintentional injuries** are the leading cause of death among college-aged individuals.
- **Homicide rates** are considerably lower than injury rates in this population.
Time-to-event analysis US Medical PG Question 5: 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)
Time-to-event analysis 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.
Time-to-event analysis US Medical PG 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
Time-to-event analysis 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.
Time-to-event analysis US Medical PG 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
Time-to-event analysis 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.
Time-to-event analysis US Medical PG Question 8: You are interested in studying the etiology of heart failure reduced ejection fraction (HFrEF) and attempt to construct an appropriate design study. Specifically, you wish to look for potential causality between dietary glucose consumption and HFrEF. Which of the following study designs would allow you to assess for and determine this causality?
- A. Cross-sectional study
- B. Case series
- C. Cohort study (Correct Answer)
- D. Case-control study
- E. Randomized controlled trial
Time-to-event analysis Explanation: ***Cohort study***
- A **cohort study** observes a group of individuals over time to identify risk factors and outcomes, allowing for the assessment of **temporal relationships** between exposure (dietary glucose) and outcome (HFrEF).
- This design is suitable for establishing a potential **causal link** as it tracks participants from exposure to outcome, enabling the calculation of incidence rates and relative risks.
*Cross-sectional study*
- A **cross-sectional study** measures exposure and outcome simultaneously at a single point in time, making it impossible to determine the **temporal sequence** of events.
- This design can only identify **associations** or correlations, not causation, as it cannot establish whether high glucose consumption preceded HFrEF.
*Case series*
- A **case series** describes characteristics of a group of patients with a particular disease or exposure, often to highlight unusual clinical features, but it lacks a **comparison group**.
- It cannot assess causality because it does not provide information on the frequency of exposure in healthy individuals or the incidence of the disease in unexposed individuals.
*Case-control study*
- A **case-control study** compares individuals with the outcome (cases) to those without the outcome (controls) to determine past exposures, which makes it prone to **recall bias**.
- While it can suggest associations, it cannot definitively establish a temporal relationship or causation as the outcome is already known when exposure is assessed.
*Randomized controlled trial*
- A **randomized controlled trial (RCT)** is the gold standard for establishing causation by randomly assigning participants to an intervention or control group, but it may not be ethical or feasible for studying long-term dietary exposures and chronic diseases like HFrEF due to the long follow-up period and complexity of diet.
- While ideal for causality, directly controlling and randomizing dietary glucose intake over decades to observe HFrEF development might be practically challenging or unethical.
Time-to-event analysis US Medical PG Question 9: A researcher wants to determine whether there is an association between CRP values and the risk of MI or cancer. Four relative risk (RR) values were plotted $(0.5,1.5,1.7,1.8)$ with respect to CRP levels. What conclusion can be drawn?
- A. CRP has no relationship
- B. CRP decreases & disease decreases
- C. CRP increases disease/cancer risk (Correct Answer)
- D. No association in first interval
- E. CRP shows protective effect in first interval
Time-to-event analysis Explanation: ***CRP increases disease/cancer risk***
- A **relative risk (RR)** greater than 1 indicates an increased risk of the outcome (MI or cancer) in the exposed group (higher CRP levels) compared to the unexposed group.
- The plots show RRs of 1.5, 1.7, and 1.8, all of which are greater than 1, consistently indicating that higher CRP levels are associated with an elevated risk for MI or cancer.
- The overall trend across the four intervals demonstrates a positive association between CRP and disease risk.
*CRP has no relationship*
- This conclusion is incorrect because three of the four plotted RR values (1.5, 1.7, 1.8) are above 1, indicating a positive association or increased risk.
- An RR of 1 signifies no relationship, but the majority of values clearly deviate from 1, showing a definite association.
*CRP decreases & disease decreases*
- While one RR value (0.5) suggests a decreased risk, the majority of the given RRs (1.5, 1.7, 1.8) are greater than 1, indicating an increased risk.
- This option would only be true if all or most RR values were less than 1, implying a protective effect, which is not the overall trend here.
*No association in first interval*
- The first interval shows an RR of 0.5. An RR of 1 indicates no association, while an RR of 0.5 actually indicates a **decreased risk or protective effect**, rather than no association.
- Therefore, stating "no association" for the first interval is inaccurate given the definition of relative risk.
*CRP shows protective effect in first interval*
- While the first interval RR of 0.5 does suggest a protective effect in isolation, this option fails to capture the **overall conclusion** from all four data points.
- When interpreting multiple RR values together, the predominant pattern (three values >1) indicates an overall increased risk, making this a misleading conclusion for the study as a whole.
Time-to-event analysis US Medical PG Question 10: A researcher wants to study the carcinogenic effects of a food additive. From the literature, he finds that 7 different types of cancers have been linked to the consumption of this food additive. He wants to study all 7 possible outcomes. He conducts interviews with people who consume food containing these additives and people who do not. He then follows both groups for several years to see if they develop any of these 7 cancers or any other health outcomes. Which of the following study models best represents this study?
- A. Cohort study (Correct Answer)
- B. Case-control study
- C. Cross-sectional study
- D. Randomized clinical trial
- E. Crossover study
Time-to-event analysis Explanation: ***Cohort study***
- This study design involves selecting a group based on their **exposure status** (consumers vs. non-consumers of the food additive) and **following them forward in time** to observe the incidence of outcomes (cancers).
- It is ideal for studying **multiple potential outcomes** from a single exposure and for establishing the **temporal relationship** between exposure and disease.
*Case-control study*
- This design starts by identifying individuals with a particular **outcome (cases)** and comparing them to individuals without the outcome (controls) to look back for **past exposures**.
- It is efficient for studying **rare diseases** or when multiple exposures are suspected for a single outcome, which is inverse to the scenario described.
*Cross-sectional study*
- This study measures both **exposure and outcome simultaneously** at a single point in time, providing a snapshot of prevalence.
- It cannot establish a **temporal relationship** between exposure and outcome and is less suitable for studying incident diseases that develop over time.
*Randomized clinical trial*
- This design involves **randomly assigning participants** to an intervention group or a control group and following them for outcomes.
- It is primarily used to evaluate the **efficacy of interventions** or treatments, not to study the carcinogenic effects of naturally occurring exposures.
*Crossover study*
- In a crossover design, participants **receive all interventions** in a specific sequence, making each subject serve as their own control.
- This design is generally used for evaluating **short-term effects of treatments** in chronic, stable conditions and is unsuitable for observing the development of diseases like cancer over extended periods.
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