Two separate investigators have conducted cohort studies to calculate the risk of lymphoma in rheumatoid arthritis patients taking anti-TNF alpha medications. They each followed patients with rheumatoid arthritis for a number of years and tracked the number of patients who were diagnosed with lymphoma. The results of the two studies are summarized in the table.
Number of patients Follow-up period Number of new cases of lymphoma
Study 1 3000 10 years 30
Study 2 300 30 years 9
Based on these results, which of the following statements about the risk of lymphoma is most accurate?
Q12
An investigator is studying the efficacy of preventative measures to reduce pesticide poisonings among Central American farmers. The investigator evaluates the effect of a ban on aldicarb, an especially neurotoxic pesticide of the carbamate class. The ban aims to reduce pesticide poisonings attributable to carbamates. The investigator followed 1,000 agricultural workers residing in Central American towns that banned aldicarb as well as 2,000 agricultural workers residing in communities that continued to use aldicarb over a period of 5 years. The results show:
Pesticide poisoning No pesticide poisoning Total
Aldicarb ban 10 990 1000
No aldicarb ban 100 1900 2000
Which of the following values corresponds to the difference in risk attributable to the ban on aldicarb?
Q13
A clinical study is performed to examine the effect of smoking on the development of pulmonary hypertension (PAH) in a sample of 40-year-old women. A group of 1,000 matched healthy subjects (500 controls; 500 smokers) were monitored for the development of (PAH) from enrollment to death. The data from the study are shown in the table below:
Group\PAH Yes No
Smokers 35 465
Controls 20 480
Which of the following is correct regarding the risk of developing PAH from this study?
Q14
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?
Q15
Researchers are studying a farming community with a high incidence of acute myelogenous leukemia (AML). A retrospective cohort study is performed looking at the relationship between exposure to a certain pesticide chemical and the risk of developing AML. In 84 patients who developed AML, 17 had exposure to the pesticide chemical. In the control group of 116 patients, 2 had exposure to the chemical. What is the relative risk of developing AML upon exposure to the pesticide in this study group?
Q16
A 45-year-old man comes to the clinic concerned about his recent exposure to radon. He heard from his co-worker that radon exposure can cause lung cancer. He brings in a study concerning the risks of radon exposure. In the study, there were 300 patients exposed to radon, and 18 developed lung cancer over a 10-year period. To compare, there were 500 patients without radon exposure and 11 developed lung cancer over the same 10-year period. If we know that 0.05% of the population has been exposed to radon, what is the attributable risk percent for developing lung cancer over a 10 year period after radon exposure?
Q17
A researcher has identified a chemical compound that she expects may contribute to the development of colorectal cancer. She designs an experiment where she exposes 70 mice to a diet containing this compound with another 50 mice in a control group that was fed a regular diet. After 9 months, the mice were evaluated for tumor development at necropsy. In total, 14 mice in the experimental group developed colorectal tumor burden, and 1 mouse in the control group developed tumors. Based on this experiment, what risk of colorectal cancer can be attributable to this chemical compound?
Q18
A prospective cohort study is conducted to evaluate the risk of pleural mesothelioma in construction workers exposed to asbestos in Los Angeles. Three hundred construction workers reporting current occupational asbestos exposure were followed alongside 300 construction workers without a history of asbestos exposure. After 8 years of follow-up, no statistically significant difference in the incidence of pleural mesothelioma was observed between the two groups (p = 0.13), even after controlling for known mesothelioma risk factors such as radiation, age, and sex. Which of the following is the most likely explanation for the observed results of this study?
Q19
You have been entrusted with the task of finding the causes of low birth weight in infants born in the health jurisdiction for which you are responsible. In 2017, there were 1,500 live births and, upon further inspection of the birth certificates, 108 of these children had a low birth weight (i.e. lower than 2,500 g), while 237 had mothers who smoked continuously during pregnancy. Further calculations have shown that the risk of low birth weight in smokers was 14% and in non-smokers, it was 7%, while the relative risk of low birth weight linked to cigarette smoking during pregnancy was 2%. In other words, women who smoked during pregnancy were twice as likely as those who did not smoke to deliver a low-weight infant. Using this data, you are also asked to calculate how much of the excess risk for low birth weight, in percentage terms, can be attributed to smoking. What is the attributable risk percentage for smoking leading to low birth weight?
Q20
Clinical study looks at the effect of childhood exposure of 2nd-hand smoking on the incidence of bronchogenic adenocarcinoma (BA). Study of 100 subjects (50 exposed to childhood 2nd-hand smoking and 50 healthy controls with no childhood exposure) involves monitoring the lifetime incidence of BA data from the study are shown in the table below:
Group\BA Dx Yes No
Exposed 18 32
Controls 7 43
Which of the following statements is correct regarding the number needed to harm (NNH) based on this study?
Cohort studies US Medical PG Practice Questions and MCQs
Question 11: Two separate investigators have conducted cohort studies to calculate the risk of lymphoma in rheumatoid arthritis patients taking anti-TNF alpha medications. They each followed patients with rheumatoid arthritis for a number of years and tracked the number of patients who were diagnosed with lymphoma. The results of the two studies are summarized in the table.
Number of patients Follow-up period Number of new cases of lymphoma
Study 1 3000 10 years 30
Study 2 300 30 years 9
Based on these results, which of the following statements about the risk of lymphoma is most accurate?
A. The risk is higher in study 1, with an incidence rate of 30 cases per 10 person-years
B. The risks are equivalent, with a prevalence of 39 cases per 3300 persons
C. The risks are equivalent, with an incidence rate of 1 case per 1000 person-years (Correct Answer)
D. The risk is higher in study 1, with a prevalence of 30 cases per 3000 patients
E. The risk is higher in study 2, with a cumulative incidence of 9 cases per 300 patients
Explanation: **The risks are equivalent, with an incidence rate of 1 case per 1000 person-years**
- To calculate the **incidence rate**, divide the number of new cases by the total person-time at risk.
- For Study 1: 30 cases / (3000 persons × 10 years) = 30 / 30,000 = 0.001 cases per person-year, or **1 case per 1000 person-years**.
- For Study 2: 9 cases / (300 persons × 30 years) = 9 / 9,000 = 0.001 cases per person-year, or **1 case per 1000 person-years**.
- Both studies yield the same incidence rate, indicating equivalent risk.
*The risk is higher in study 1, with an incidence rate of 30 cases per 10 person-years*
- The calculation "30 cases per 10 person-years" incorrectly uses the follow-up period instead of the total person-time at risk across all participants.
- This calculation does not accurately reflect the **incidence rate** as it doesn't account for the number of individuals in the study.
*The risks are equivalent, with a prevalence of 39 cases per 3300 persons*
- **Prevalence** refers to existing cases at a specific point in time, not new cases over a period.
- This calculation incorrectly combines data from two separate studies as if it were a single point prevalence, which is methodologically incorrect.
*The risk is higher in study 1, with a prevalence of 30 cases per 3000 patients*
- This statement uses a calculation that resembles **cumulative incidence** (new cases divided by initial population) for Study 1, but incorrectly labels it as prevalence.
- A cumulative incidence of 30/3000 = 0.01 (or 1%) for Study 1 does not account for the duration of follow-up, making direct comparison with Study 2 (which has a 30-year follow-up) inappropriate.
*The risk is higher in study 2, with a cumulative incidence of 9 cases per 300 patients*
- Study 2 has a **cumulative incidence** of 9/300 = 0.03 (or 3%) over 30 years.
- Comparing cumulative incidence directly between studies with different follow-up durations (10 years vs. 30 years) is not appropriate for assessing the underlying risk rate, as it does not account for the time component.
Question 12: An investigator is studying the efficacy of preventative measures to reduce pesticide poisonings among Central American farmers. The investigator evaluates the effect of a ban on aldicarb, an especially neurotoxic pesticide of the carbamate class. The ban aims to reduce pesticide poisonings attributable to carbamates. The investigator followed 1,000 agricultural workers residing in Central American towns that banned aldicarb as well as 2,000 agricultural workers residing in communities that continued to use aldicarb over a period of 5 years. The results show:
Pesticide poisoning No pesticide poisoning Total
Aldicarb ban 10 990 1000
No aldicarb ban 100 1900 2000
Which of the following values corresponds to the difference in risk attributable to the ban on aldicarb?
A. 0.04 (Correct Answer)
B. 0.19
C. 0.8
D. 90
E. 0.2
Explanation: ***0.04***
- The **risk in the ban group** (unexposed to aldicarb) is 10/1000 = 0.01
- The **risk in the no-ban group** (exposed to aldicarb) is 100/2000 = 0.05
- The **attributable risk (risk difference)** is calculated as: Risk in no-ban group - Risk in ban group = 0.05 - 0.01 = **0.04**
- This represents the absolute risk reduction achieved by implementing the ban, meaning the ban prevented 4 additional cases per 100 workers
*0.19*
- This value does not correspond to any standard epidemiological measure calculated from this data
- Not the risk difference, relative risk, or odds ratio
*0.8*
- This represents the **relative risk reduction**: (0.05 - 0.01)/0.05 = 0.8 or 80%
- While this shows the ban reduced risk by 80% relative to baseline, the question specifically asks for the **difference in risk** (attributable risk), not the proportional reduction
*90*
- This represents the **absolute number of excess cases** in the no-ban group that could have been prevented
- Calculated as: (100 cases in no-ban group) - (20 cases that would be expected if ban-group rate applied to 2000 workers) = 80, or comparing absolute numbers: 100 - 10 = 90
- However, attributable risk is expressed as a **rate or proportion**, not as an absolute count
*0.2*
- This value does not match any standard calculation from the provided data
- May result from an error in calculation or confusion with other epidemiological measures
Question 13: A clinical study is performed to examine the effect of smoking on the development of pulmonary hypertension (PAH) in a sample of 40-year-old women. A group of 1,000 matched healthy subjects (500 controls; 500 smokers) were monitored for the development of (PAH) from enrollment to death. The data from the study are shown in the table below:
Group\PAH Yes No
Smokers 35 465
Controls 20 480
Which of the following is correct regarding the risk of developing PAH from this study?
A. The lifetime absolute risk increase of developing PAH in female smokers is 3%. (Correct Answer)
B. The lifetime absolute risk of developing PAH in healthy non-smoking women is 3%.
C. The increase in the absolute risk of developing PAH by quitting smoking is 75%.
D. The absolute risk of developing PAH in smokers versus controls is 1.75.
E. The lifetime absolute risk of developing PAH in healthy nonsmoking women is 5.5%.
Explanation: ***The lifetime absolute risk increase of developing PAH in female smokers is 3%.***
- The **absolute risk reduction** (ARR) is the difference in risk between the exposed group (smokers) and the unexposed group (controls). For smokers, the risk of PAH is 35/500 = 0.07 (7%). For controls, the risk is 20/500 = 0.04 (4%). The absolute risk increase for smokers is 7% - 4% = **3%**.
- This value represents the additional risk of developing PAH attributable to smoking in this population.
*The lifetime absolute risk of developing PAH in healthy non-smoking women is 3%.*
- The **absolute risk** of developing PAH in **healthy non-smoking women (controls)** is 20/500, which equals **0.04 or 4%**.
- The 3% presented in this option is incorrect; it actually represents the **absolute risk increase** for smokers.
*The increase in the absolute risk of developing PAH by quitting smoking is 75%.*
- This statement implies a calculation of **relative risk reduction** or similar, but the value of 75% is not directly obtained from the provided data as an increase in absolute risk by quitting.
- Quitting smoking would lead to a reduction in risk, not an increase, and 75% does not correspond to a direct calculation of risk difference or ratio.
*The absolute risk of developing PAH in smokers versus controls is 1.75.*
- An absolute risk value cannot be 1.75, as risk is typically expressed as a **proportion or percentage (0 to 1 or 0% to 100%)**.
- This value of 1.75 might be the **relative risk**, calculated as (Risk in smokers / Risk in controls) = (0.07 / 0.04) = 1.75. However, this is a **relative risk**, not an absolute risk.
*The lifetime absolute risk of developing PAH in healthy nonsmoking women is 5.5%.*
- The **absolute risk** of developing PAH in **healthy non-smoking women (controls)** is 20/500, which equals **0.04 or 4%**.
- The value of 5.5% is incorrect for the control group's absolute risk.
Question 14: 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
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.
Question 15: Researchers are studying a farming community with a high incidence of acute myelogenous leukemia (AML). A retrospective cohort study is performed looking at the relationship between exposure to a certain pesticide chemical and the risk of developing AML. In 84 patients who developed AML, 17 had exposure to the pesticide chemical. In the control group of 116 patients, 2 had exposure to the chemical. What is the relative risk of developing AML upon exposure to the pesticide in this study group?
A. Number of exposed with AML (17) divided by the total number of AML cases (84)
B. Total number of cases (84) divided by the total number of study participants (200)
C. Probability of AML among exposed (17/19) divided by probability of AML among unexposed (67/181) (Correct Answer)
D. Odds of exposure in the cases (17/67) divided by odds of exposure in the controls (2/114)
E. Prevalence of cases (84/200) divided by prevalence of controls (116/200)
Explanation: ***Probability of AML among exposed (17/19) divided by probability of AML among unexposed (67/181)***
- This calculation correctly applies the formula for **relative risk** in a cohort study. It compares the **incidence of AML in the exposed group** to the **incidence of AML in the unexposed group**.
- The number **17** represents the exposed individuals who developed AML, and the total exposed population is **19** (17 cases + 2 controls). The number **67** represents the unexposed individuals who developed AML (84 total AML cases - 17 exposed AML cases), and the total unexposed population is **181** (116 total controls + 67 unexposed AML cases - 2 exposed controls).
*Number of exposed with AML (17) divided by the total number of AML cases (84)*
- This calculation represents the **proportion of AML cases that were exposed**, not the relative risk.
- It does not account for the **total number of exposed or unexposed individuals** in the study population.
*Total number of cases (84) divided by the total number of study participants (200)*
- This calculation gives the **overall incidence of AML** in the entire study population, not the relative risk associated with pesticide exposure.
- Relative risk specifically compares **risk between exposed and unexposed groups**.
*Odds of exposure in the cases (17/67) divided by odds of exposure in the controls (2/114)*
- This calculation determines the **odds ratio**, which is used in **case-control studies**, not the relative risk used in cohort studies.
- The odds ratio estimates relative risk when the outcome is rare, but it is not a direct measure of relative risk.
*Prevalence of cases (84/200) divided by prevalence of controls (116/200)*
- This calculation is incorrect for determining relative risk. It compares the **overall proportion of cases to the overall proportion of controls** from the entire study population.
- It does not differentiate the incidence of disease between the **exposed and unexposed groups**.
Question 16: A 45-year-old man comes to the clinic concerned about his recent exposure to radon. He heard from his co-worker that radon exposure can cause lung cancer. He brings in a study concerning the risks of radon exposure. In the study, there were 300 patients exposed to radon, and 18 developed lung cancer over a 10-year period. To compare, there were 500 patients without radon exposure and 11 developed lung cancer over the same 10-year period. If we know that 0.05% of the population has been exposed to radon, what is the attributable risk percent for developing lung cancer over a 10 year period after radon exposure?
A. 3.8%
B. 0.31%
C. 2.2%
D. 6.0%
E. 63.3% (Correct Answer)
Explanation: ***63.3%***
- The **attributable risk percent (ARP)** quantifies the proportion of disease in the exposed group that is attributable to the exposure. It is calculated as [(Incidence in exposed - Incidence in unexposed) / Incidence in exposed] * 100.
- In this case, **Incidence in exposed (radon)** = 18/300 = 0.06 or 6%. **Incidence in unexposed** = 11/500 = 0.022 or 2.2%. Therefore, ARP = [(0.06 - 0.022) / 0.06] * 100 = (0.038 / 0.06) * 100 = **63.3%**.
*3.8%*
- This value represents the difference in the **absolute risk** or incidence between the exposed and unexposed groups (6% - 2.2% = 3.8%).
- It does not represent the proportion of disease in the exposed group that is due to the exposure.
*0.31%*
- This value is not derived from the given data using standard epidemiological formulas for attributable risk percent.
- It is possibly a miscalculation or an irrelevant measure in this context.
*2.2%*
- This value represents the **incidence of lung cancer in the unexposed group** (11/500 = 0.022 or 2.2%).
- It is a component of the ARP calculation but not the ARP itself.
*6.0%*
- This value represents the **incidence of lung cancer in the radon-exposed group** (18/300 = 0.06 or 6%).
- It is used in the numerator and denominator for calculating the attributable risk percent but is not the final ARP.
Question 17: A researcher has identified a chemical compound that she expects may contribute to the development of colorectal cancer. She designs an experiment where she exposes 70 mice to a diet containing this compound with another 50 mice in a control group that was fed a regular diet. After 9 months, the mice were evaluated for tumor development at necropsy. In total, 14 mice in the experimental group developed colorectal tumor burden, and 1 mouse in the control group developed tumors. Based on this experiment, what risk of colorectal cancer can be attributable to this chemical compound?
A. 22.0%
B. 2.0%
C. 12.5%
D. 18.0% (Correct Answer)
E. 20.0%
Explanation: ***18.0%***
- The **attributable risk (AR)** is calculated as the **incidence in the exposed group (Ie)** minus the **incidence in the unexposed group (Iu)**.
- In this case, **Ie = 14/70 = 0.20** and **Iu = 1/50 = 0.02**. Therefore, **AR = 0.20 - 0.02 = 0.18**, or **18.0%**.
*22.0%*
- This value might result from an incorrect calculation or misinterpretation of the attributable risk formula.
- It does not correctly represent the difference in risk between the exposed and unexposed groups.
*2.0%*
- This represents the **incidence of colorectal tumors in the control group (Iu)**, not the attributable risk.
- The attributable risk accounts for the excess risk specifically due to the exposure.
*12.5%*
- This value is not derived from the standard formula for attributable risk using the provided data.
- It might represent a misunderstanding of how to calculate risk difference from incidence rates.
*20.0%*
- This represents the **incidence of colorectal tumors in the experimental group (Ie)**, not the attributable risk.
- The attributable risk needs to subtract the background risk observed in the unexposed group.
Question 18: A prospective cohort study is conducted to evaluate the risk of pleural mesothelioma in construction workers exposed to asbestos in Los Angeles. Three hundred construction workers reporting current occupational asbestos exposure were followed alongside 300 construction workers without a history of asbestos exposure. After 8 years of follow-up, no statistically significant difference in the incidence of pleural mesothelioma was observed between the two groups (p = 0.13), even after controlling for known mesothelioma risk factors such as radiation, age, and sex. Which of the following is the most likely explanation for the observed results of this study?
A. Berkson bias
B. Lead-time bias
C. Observer effect
D. Latency period (Correct Answer)
E. Length-time bias
Explanation: ***Latency period***
- Asbestos-related pleural mesothelioma has a **long latency period**, typically 20-50 years, between initial exposure and the development of clinical disease.
- An 8-year follow-up period is likely too short to observe a **statistically significant incidence** of mesothelioma, even in an exposed cohort.
*Berkson bias*
- This is a form of **selection bias** that occurs in studies using hospital-based controls, where exposure rates may differ between hospital patients and the general population due to varying admission probabilities for different diseases.
- The given study is a **prospective cohort study** of a specific occupational group, not a case-control study based in a hospital, making Berkson bias unlikely.
*Lead-time bias*
- This bias occurs when early detection of a disease (e.g., through screening) falsely appears to prolong survival due to the **earlier diagnosis**, not due to an actual improvement in the course of the disease.
- The study is assessing the **incidence** of mesothelioma in exposed vs. unexposed groups, not comparing survival outcomes based on screening, so lead-time bias is not relevant here.
*Observer effect*
- Also known as the **Hawthorne effect**, this occurs when individuals modify an aspect of their behavior in response to their awareness of being observed.
- The study is observing the development of a disease (mesothelioma), which is not subject to behavioral changes due to observation.
*Length-time bias*
- This bias arises in screening programs where individuals with **slowly progressing diseases** are more likely to be detected by screening because their disease is present for a longer "detectable" period.
- The study is focused on the **incidence** of a disease in a cohort, not on the effectiveness or impact of a screening program, rendering length-time bias an irrelevant explanation.
Question 19: You have been entrusted with the task of finding the causes of low birth weight in infants born in the health jurisdiction for which you are responsible. In 2017, there were 1,500 live births and, upon further inspection of the birth certificates, 108 of these children had a low birth weight (i.e. lower than 2,500 g), while 237 had mothers who smoked continuously during pregnancy. Further calculations have shown that the risk of low birth weight in smokers was 14% and in non-smokers, it was 7%, while the relative risk of low birth weight linked to cigarette smoking during pregnancy was 2%. In other words, women who smoked during pregnancy were twice as likely as those who did not smoke to deliver a low-weight infant. Using this data, you are also asked to calculate how much of the excess risk for low birth weight, in percentage terms, can be attributed to smoking. What is the attributable risk percentage for smoking leading to low birth weight?
A. 40%
B. 30%
C. 20%
D. 10%
E. 50% (Correct Answer)
Explanation: ***50%***
- This value is calculated using the formula for **attributable risk percent (ARP)** in the exposed group: ARP = ((Risk in exposed - Risk in unexposed) / Risk in exposed) × 100.
- Given that the risk of low birth weight in smokers (exposed) is 14% and in non-smokers (unexposed) is 7%, the calculation is ((0.14 - 0.07) / 0.14) × 100 = (0.07 / 0.14) × 100 = **0.50 × 100 = 50%**.
*40%*
- This percentage does not align with the provided risk values for low birth weight in smokers (14%) and non-smokers (7%).
- A calculation of ((0.14 - 0.07) / 0.14) * 100 does not yield 40%.
*30%*
- This value is incorrect, as it would suggest a smaller difference in risk between the exposed and unexposed groups relative to the risk in the exposed group than what is presented in the problem.
- The calculated attributable risk percent is higher than 30%.
*20%*
- This option is significantly lower than the true attributable risk percent derived from the given risk figures.
- It would imply a much weaker association between smoking and low birth weight in terms of excess risk than what is calculated.
*10%*
- This value is substantially different from the correct calculation and would suggest a very minor attributable risk.
- The attributable risk percent for smoking leading to low birth weight is much higher than 10% based on the provided data.
Question 20: Clinical study looks at the effect of childhood exposure of 2nd-hand smoking on the incidence of bronchogenic adenocarcinoma (BA). Study of 100 subjects (50 exposed to childhood 2nd-hand smoking and 50 healthy controls with no childhood exposure) involves monitoring the lifetime incidence of BA data from the study are shown in the table below:
Group\BA Dx Yes No
Exposed 18 32
Controls 7 43
Which of the following statements is correct regarding the number needed to harm (NNH) based on this study?
A. If the absolute risk in the exposed group increases, the NNH increases.
B. If the incidence of BA increases in the control group, the NNH will decrease.
C. The NNH is inversely correlated with the relative risk increase. (Correct Answer)
D. If the incidence of BA increases in the experimental group, the NNH will increase.
E. The NNH is approximately 4.5.
Explanation: ***The NNH is inversely correlated with the relative risk increase.***
- The **number needed to harm (NNH)** is defined as 1 divided by the **absolute risk increase (ARI)**. The formula is NNH = 1 / ARI. Since **relative risk increase (RRI)** is directly proportional to **absolute risk increase (ARI)** when baseline risk is constant, NNH is inversely correlated with RRI.
- Mathematically, NNH is 1/(Incidence in exposed - Incidence in unexposed). A larger increase in relative risk implies a larger **absolute risk increase**, which would result in a smaller NNH.
*The NNH is approximately 4.5.*
- The **incidence** in the exposed group is 18/50 = 0.36. The **incidence** in the control group is 7/50 = 0.14.
- The **absolute risk increase (ARI)** = Incidence (exposed) - Incidence (control) = 0.36 - 0.14 = 0.22. Therefore, NNH = 1/0.22 ≈ 4.5. This option is incorrect because it accurately calculates the NNH, making it a factually correct statement, but it is not the **best answer** to what the question asks.
*If the absolute risk in the exposed group increases, the NNH increases.*
- An increase in the **absolute risk in the exposed group** would lead to a larger **absolute risk increase (ARI)**, assuming the control group risk remains constant or increases less proportionally.
- Since NNH = 1/ARI, a larger ARI would result in a **smaller NNH**, not an increase.
*If the incidence of BA increases in the control group, the NNH will decrease.*
- If the **incidence of BA in the control group** increases, the **absolute risk increase (ARI)** (Incidence in exposed - Incidence in control) would likely decrease (assuming the exposed incidence stays the same or increases less proportionally).
- A decrease in ARI would lead to an **increase in NNH**, not a decrease, because NNH is inversely related to ARI.
*If the incidence of BA increases in the experimental group, the NNH will increase.*
- An increase in the **incidence of BA in the experimental (exposed) group** would lead to a larger **absolute risk increase (ARI)**, assuming the control group incidence remains constant.
- A larger ARI would result in a **smaller NNH**, not an increase, as NNH is inversely proportional to ARI.