Strengths and limitations of cohort studies US Medical PG Practice Questions and MCQs
Practice US Medical PG questions for Strengths and limitations of cohort studies. These multiple choice questions (MCQs) cover important concepts and help you prepare for your exams.
Strengths and limitations of cohort studies US Medical PG Question 1: A 25-year-old man with a genetic disorder presents for genetic counseling because he is concerned about the risk that any children he has will have the same disease as himself. Specifically, since childhood he has had difficulty breathing requiring bronchodilators, inhaled corticosteroids, and chest physiotherapy. He has also had diarrhea and malabsorption requiring enzyme replacement therapy. If his wife comes from a population where 1 in 10,000 people are affected by this same disorder, which of the following best represents the likelihood a child would be affected as well?
- A. 0.01%
- B. 2%
- C. 0.5%
- D. 1% (Correct Answer)
- E. 50%
Strengths and limitations of cohort studies Explanation: ***Correct Option: 1%***
- The patient's symptoms (difficulty breathing requiring bronchodilators, inhaled corticosteroids, and chest physiotherapy; diarrhea and malabsorption requiring enzyme replacement therapy) are classic for **cystic fibrosis (CF)**, an **autosomal recessive disorder**.
- For an autosomal recessive disorder with a prevalence of 1 in 10,000 in the general population, **q² = 1/10,000**, so **q = 1/100 = 0.01**. The carrier frequency **(2pq)** is approximately **2q = 2 × (1/100) = 1/50 = 0.02**.
- The affected man is **homozygous recessive (aa)** and will always pass on the recessive allele. His wife has a **1/50 chance of being a carrier (Aa)**. If she is a carrier, she has a **1/2 chance of passing on the recessive allele**.
- Therefore, the probability of an affected child = **(Probability wife is a carrier) × (Probability wife passes recessive allele) = 1/50 × 1/2 = 1/100 = 1%**.
*Incorrect Option: 0.01%*
- This percentage is too low and does not correctly account for the carrier frequency in the population and the probability of transmission from a carrier mother.
*Incorrect Option: 2%*
- This represents approximately the carrier frequency (1/50 ≈ 2%), but does not account for the additional 1/2 probability that a carrier mother would pass on the recessive allele.
*Incorrect Option: 0.5%*
- This value would be correct if the carrier frequency were 1/100 instead of 1/50, which does not match the given population prevalence.
*Incorrect Option: 50%*
- **50%** would be the risk if both parents were carriers of an autosomal recessive disorder (1/4 chance = 25% for affected, but if we know one parent passes the allele, conditional probability changes). More accurately, 50% would apply if the disorder were **autosomal dominant** with one affected parent, which is not the case here.
Strengths and limitations of cohort studies US Medical PG Question 2: A scientist is studying the characteristics of a newly discovered infectious disease in order to determine its features. He calculates the number of patients that develop the disease over several months and finds that on average 75 new patients become infected per month. Furthermore, he knows that the disease lasts on average 2 years before patients are either cured or die from the disease. If the population being studied consists of 7500 individuals, which of the following is the prevalence of the disease?
- A. 0.24 (Correct Answer)
- B. 0.02
- C. 0.12
- D. 0.005
- E. 0.01
Strengths and limitations of cohort studies Explanation: ***0.24***
- Prevalence is calculated as the **number of existing cases** divided by the **total population**. The number of existing cases is estimated by multiplying the **incidence rate** (75 new cases/month) by the **duration of the disease** (2 years or 24 months): 75 cases/month * 24 months = 1800 cases.
- The prevalence is then 1800 cases / 7500 individuals = **0.24**.
*0.02*
- This value might be obtained by incorrectly using only the monthly incidence or by performing **incorrect calculations** involving the duration and total population.
- It does not account for the **cumulative effect** of new cases over the entire disease duration.
*0.12*
- This answer might result from miscalculating the **duration of the disease** (e.g., using 1 year instead of 2 years), leading to an underestimation of the total existing cases.
- It suggests an error in converting the **duration from years to months** when multiplying by the monthly incidence.
*0.005*
- This value is significantly lower than the correct prevalence, suggesting a major error in calculating the total number of cases or incorrectly dividing the total cases by the entire population.
- It does not properly reflect the contribution of new cases over the **duration of the disease**.
*0.01*
- This result is likely derived from an incorrect application of the incidence rate or a misunderstanding of how the duration of the disease impacts the **total number of prevalent cases**.
- It's a calculation error that significantly underestimates the **true disease burden**.
Strengths and limitations of cohort studies US Medical PG Question 3: The APPLE study investigators are currently preparing for a 30-year follow-up evaluation. They are curious about the number of participants who will partake in follow-up interviews. The investigators noted that of the 83 participants who participated in the APPLE study's 20-year follow-up, 62 were in the treatment group and 21 were in the control group. Given the unequal distribution of participants between groups at follow-up, this finding raises concerns for which of the following?
- A. Volunteer bias
- B. Reporting bias
- C. Inadequate sample size
- D. Attrition bias (Correct Answer)
- E. Lead-time bias
Strengths and limitations of cohort studies Explanation: ***Attrition bias***
- **Attrition bias** occurs when participants drop out of a study, especially if the dropout rate differs between the intervention and control groups, which can lead to a **skewed comparison** of outcomes.
- The unequal distribution of participants (62 vs. 21) between the treatment and control groups at the 20-year follow-up suggests that a disproportionate number of participants may have dropped out of one group, thus leading to attrition bias.
*Volunteer bias*
- **Volunteer bias** occurs when individuals who volunteer for a study differ significantly from the general population or those who decline to participate, potentially affecting the study's **generalizability**.
- This scenario describes differences in retention *after* initial participation, not differences in initial willingness to join.
*Reporting bias*
- **Reporting bias** refers to the selective reporting of study findings, where positive or statistically significant results are more likely to be published or emphasized than negative or non-significant ones, which can distort the overall evidence base.
- This bias relates to how results are disseminated, not to differential dropout rates or participant retention in a study.
*Inadequate sample size*
- **Inadequate sample size** means that the number of participants in a study is too small to detect a statistically significant effect if one truly exists, leading to a lack of **statistical power**.
- While the overall number of participants at follow-up might be small, the primary concern here is the *unequal distribution* between groups, indicating a problem with participant retention rather than just a low total count.
*Lead-time bias*
- **Lead-time bias** occurs when early detection of a disease (e.g., through screening) makes survival appear longer than it actually is, without necessarily prolonging the patient's life, by advancing the **point of diagnosis**.
- This bias is relevant to screening programs and disease detection, not to the differential dropout rates observed in a longitudinal study.
Strengths and limitations of cohort studies US Medical PG Question 4: A group of environmental health scientists recently performed a nationwide cross-sectional study that investigated the risk of head and neck cancers in patients with a history of cigar and pipe smoking. In collaboration with three teams of epidemiologists that have each conducted similar cross-sectional studies in their respective countries, they have agreed to contribute their data to an international pooled analysis of the relationship between non-cigarette tobacco consumption and prevalence of head and neck cancers. Which of the following statements regarding the pooled analysis in comparison to the individual studies is true?
- A. The results are less precise.
- B. It overcomes limitations in the quality of individual studies.
- C. It is able to provide evidence of causality.
- D. The level of clinical evidence is lower.
- E. The likelihood of type II errors is decreased. (Correct Answer)
Strengths and limitations of cohort studies Explanation: ***The likelihood of type II errors is decreased.***
- A pooled analysis or **meta-analysis** combines data from multiple studies, significantly increasing the **overall sample size**.
- A larger sample size enhances the statistical power, making it less likely to miss a real effect and thus reducing the probability of **Type II errors** (false negatives).
*The results are less precise.*
- Combining data from multiple studies in a **pooled analysis** generally leads to **more precise estimates** due to the larger sample size and increased statistical power.
- Increased precision is reflected in narrower confidence intervals, offering a more reliable estimate of the effect.
*It overcomes limitations in the quality of individual studies.*
- A pooled analysis **does not inherently overcome limitations** in the design, methodology, or quality of the individual studies included.
- If the original studies have significant biases or flaws, these limitations can be propagated or even amplified in the pooled results.
*It is able to provide evidence of causality.*
- Pooled analyses of **cross-sectional studies**, like the ones described, can identify **associations** but cannot establish **causality**.
- Cross-sectional studies measure exposure and outcome simultaneously, making it impossible to determine the temporal sequence necessary to infer cause and effect.
*The level of clinical evidence is lower.*
- Combining multiple studies, especially well-conducted ones, in a pooled analysis or **meta-analysis** generally **increases the level of clinical evidence**, placing it higher than individual observational studies.
- This is because a pooled analysis offers a more robust and comprehensive view of the existing evidence.
Strengths and limitations of cohort studies US Medical PG Question 5: A 28-year-old male presents to his primary care physician with complaints of intermittent abdominal pain and alternating bouts of constipation and diarrhea. His medical chart is not significant for any past medical problems or prior surgeries. He is not prescribed any current medications. Which of the following questions would be the most useful next question in eliciting further history from this patient?
- A. "Does the diarrhea typically precede the constipation, or vice-versa?"
- B. "Is the diarrhea foul-smelling?"
- C. "Please rate your abdominal pain on a scale of 1-10, with 10 being the worst pain of your life"
- D. "Are the symptoms worse in the morning or at night?"
- E. "Can you tell me more about the symptoms you have been experiencing?" (Correct Answer)
Strengths and limitations of cohort studies Explanation: ***Can you tell me more about the symptoms you have been experiencing?***
- This **open-ended question** encourages the patient to provide a **comprehensive narrative** of their symptoms, including details about onset, frequency, duration, alleviating/aggravating factors, and associated symptoms, which is crucial for diagnosis.
- In a patient presenting with vague, intermittent symptoms like alternating constipation and diarrhea, allowing them to elaborate freely can reveal important clues that might not be captured by more targeted questions.
*Does the diarrhea typically precede the constipation, or vice-versa?*
- While knowing the sequence of symptoms can be helpful in understanding the **pattern of bowel dysfunction**, it is a very specific question that might overlook other important aspects of the patient's experience.
- It prematurely narrows the focus without first obtaining a broad understanding of the patient's overall symptomatic picture.
*Is the diarrhea foul-smelling?*
- Foul-smelling diarrhea can indicate **malabsorption** or **bacterial overgrowth**, which are important to consider in some gastrointestinal conditions.
- However, this is a **specific symptom inquiry** that should follow a more general exploration of the patient's symptoms, as it may not be relevant if other crucial details are missed.
*Please rate your abdominal pain on a scale of 1-10, with 10 being the worst pain of your life*
- Quantifying pain intensity is useful for assessing the **severity of discomfort** and monitoring changes over time.
- However, for a patient with intermittent rather than acute, severe pain, understanding the **character, location, and triggers** of the pain is often more diagnostically valuable than just a numerical rating initially.
*Are the symptoms worse in the morning or at night?*
- Diurnal variation can be relevant in certain conditions, such as inflammatory bowel diseases where nocturnal symptoms might be more concerning, or functional disorders whose symptoms might be stress-related.
- This is another **specific question** that should come after gathering a more complete initial picture of the patient's symptoms to ensure no key information is overlooked.
Strengths and limitations of cohort studies US Medical PG Question 6: A scientist is designing a study to determine whether eating a new diet is able to lower blood pressure in a group of patients. In particular, he believes that starting the diet may help decrease peak blood pressures throughout the day. Therefore, he will equip study participants with blood pressure monitors and follow pressure trends over a 24-hour period. He decides that after recruiting subjects, he will start them on either the new diet or a control diet and follow them for 1 month. After this time, he will switch patients onto the other diet and follow them for an additional month. He will analyze the results from the first month against the results from the second month for each patient. This type of study design is best at controlling for which of the following problems with studies?
- A. Hawthorne effect
- B. Recall bias
- C. Confounding (Correct Answer)
- D. Selection bias
- E. Pygmalion effect
Strengths and limitations of cohort studies Explanation: ***Confounding***
- This **crossover design** (switching patients to the other diet) effectively controls for **confounding variables** by making each patient their own control, ensuring that inherent patient characteristics do not bias the comparison between diets.
- By comparing the effects of both diets within the same individual, individual variability in factors such as genetics, lifestyle, and other co-morbidities are accounted for, reducing their potential as confounders.
*Hawthorne effect*
- The **Hawthorne effect** refers to subjects modifying their behavior in response to being observed, which this study design does not specifically address or eliminate.
- While patients are being monitored, the design aims to compare the diets' effects, not to prevent behavioral changes due to observation itself.
*Recall bias*
- **Recall bias** occurs when participants' memories of past events are inaccurate, often influenced by their current health status or beliefs.
- This study measures **real-time blood pressure** data, not relying on recollection of past exposures or outcomes, thereby mitigating recall bias.
*Selection bias*
- **Selection bias** arises from non-random selection of participants into study groups, leading to systematic differences between groups.
- While patient recruitment could introduce selection bias into the overall study population, the **crossover design** itself helps control for differences between treatment arms because all participants eventually receive both treatments.
*Pygmalion effect*
- The **Pygmalion effect** (or observer-expectancy effect) describes phenomena where higher expectations lead to increased performance, usually from a researcher influencing a subject.
- This effect is not directly addressed by the crossover design; the design focuses on controlling for patient-specific confounders rather than investigator bias in expectations.
Strengths and limitations of cohort studies US Medical PG Question 7: In recent years, psoriasis has been identified as a risk factor for cardiovascular disease. A researcher conducted a study in which he identified 200 patients with psoriasis and 200 patients without psoriasis. The patients were followed for 10 years. At the end of this period, participants' charts were reviewed for myocardial infarction during this time interval.
Myocardial infarction No myocardial infarction Total
Psoriasis 12 188 200
No psoriasis 4 196 200
Total 16 384 400
What is the 10-year risk of myocardial infarction in participants with psoriasis?
- A. 0.75
- B. 0.04
- C. 0.5
- D. 0.06 (Correct Answer)
- E. 0.02
Strengths and limitations of cohort studies Explanation: ***0.06***
- The **risk of myocardial infarction** in participants with psoriasis is calculated by dividing the number of psoriasis patients who had a myocardial infarction by the total number of psoriasis patients.
- This calculation is 12 (myocardial infarctions in psoriasis group) / 200 (total psoriasis patients) = **0.06 or 6%**.
- This represents the **cumulative incidence** or **absolute risk** in the exposed cohort over 10 years.
*0.75*
- This value represents the **proportion of all MI cases that occurred in the psoriasis group**: 12/16 = 0.75.
- This is not the same as risk, which requires the denominator to be the total at-risk population (all psoriasis patients), not just those with the outcome.
*0.04*
- This value represents the **risk of myocardial infarction in the control group** (no psoriasis): 4/200 = 0.02, not 0.04.
- However, 0.04 could represent 2 × 0.02, which has no meaningful epidemiological interpretation for this study.
*0.5*
- This value does not correspond to any standard epidemiological measure from the given data.
- It might represent a miscalculation or confusion with other statistical concepts.
*0.02*
- This value represents the **risk of myocardial infarction in the unexposed group** (no psoriasis): 4/200 = 0.02 or 2%.
- The question specifically asks for the risk in the psoriasis group, not the control group.
Strengths and limitations of cohort studies US Medical PG Question 8: A population is studied for risk factors associated with testicular cancer. Alcohol exposure, smoking, dietary factors, social support, and environmental exposure are all assessed. The researchers are interested in the incidence and prevalence of the disease in addition to other outcomes. Which pair of studies would best assess the 1. incidence and 2. prevalence?
- A. 1. Prospective cohort study 2. Cross sectional study (Correct Answer)
- B. 1. Prospective cohort study 2. Retrospective cohort study
- C. 1. Cross sectional study 2. Retrospective cohort study
- D. 1. Case-control study 2. Prospective cohort study
- E. 1. Clinical trial 2. Cross sectional study
Strengths and limitations of cohort studies Explanation: ***1. Prospective cohort study 2. Cross sectional study***
- A **prospective cohort study** is ideal for measuring **incidence** (new cases over time) because it follows a group of individuals forward in time to observe who develops the disease.
- A **cross-sectional study** is suitable for measuring **prevalence** (existing cases at a specific point in time) as it surveys a population at one moment to determine the proportion with the disease.
*1. Prospective cohort study 2. Retrospective cohort study*
- A **retrospective cohort study** assesses past exposures and outcomes and can measure incidence, but it is not the primary choice for prevalence.
- While a prospective cohort study is appropriate for incidence, a retrospective cohort study is less suited for determining current prevalence.
*1. Cross sectional study 2. Retrospective cohort study*
- A **cross-sectional study** measures prevalence, not incidence, as it captures disease status at a single point in time.
- A **retrospective cohort study** looks back in time to identify past exposures and subsequent outcomes, which is not the best method for current prevalence.
*1. Case-control study 2. Prospective cohort study*
- A **case-control study** compares exposures between individuals with a disease (cases) and those without (controls) and is best for studying rare diseases and estimating odds ratios, not incidence or prevalence directly.
- A **prospective cohort study** is suitable for incidence, but a case-control study is not for incidence or prevalence.
*1. Clinical trial 2. Cross sectional study*
- A **clinical trial** is an experimental study designed to test the efficacy of interventions and is not primarily used to measure disease incidence or prevalence in a general population.
- While a cross-sectional study is appropriate for prevalence, a clinical trial is not designed for incidence measurement.
Strengths and limitations of cohort studies US Medical PG Question 9: 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
Strengths and limitations of cohort studies 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.
Strengths and limitations of cohort studies US Medical PG Question 10: 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
Strengths and limitations of cohort studies 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.
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