NAPLEX Quiz: Biostatistical And Pharmacoeconomic Measures
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Biostatistical And Pharmacoeconomic MeasuresQuestion 1 of 20

A comparative study of 900 patients (mean age 55 years; 58% female) with asthma compared Add-on Therapy C vs Add-on Therapy D for preventing exacerbations over 1 year. Exacerbation rates were 0.80 vs 0.90 per patient-year (rate ratio 0.89; 95% CI 0.80 to 0.99; p = 0.04). Annual drug costs were $3,200 (C) vs $2,600 (D). How do the confidence intervals affect the interpretation of the study?

Because the 95% CI is entirely below 1.0, Therapy C shows a statistically significant reduction in exacerbation rate compared with Therapy D
Because the CI is below 1.0, Therapy C must be clinically large enough to justify any cost
The CI means 95% of patients will have a personal rate ratio between 0.80 and 0.99
Because the CI is close to 1.0, the result is automatically not statistically significant
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NAPLEX Quiz

NAPLEX Quiz: Biostatistical And Pharmacoeconomic Measures

Practice Biostatistical And Pharmacoeconomic Measures in NAPLEX with focused quiz questions that help you check what you know, review explanations, and build confidence with test-style prompts.

What this quiz covers

This quiz focuses on Biostatistical And Pharmacoeconomic Measures, giving you a quick way to practice the rules, question types, and explanations that matter most for NAPLEX.

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Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

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Question 1

A comparative study of 900 patients (mean age 55 years; 58% female) with asthma compared Add-on Therapy C vs Add-on Therapy D for preventing exacerbations over 1 year. Exacerbation rates were 0.80 vs 0.90 per patient-year (rate ratio 0.89; 95% CI 0.80 to 0.99; p = 0.04). Annual drug costs were $3,200 (C) vs $2,600 (D). How do the confidence intervals affect the interpretation of the study?

  1. Because the 95% CI is entirely below 1.0, Therapy C shows a statistically significant reduction in exacerbation rate compared with Therapy D (correct answer)
  2. Because the CI is below 1.0, Therapy C must be clinically large enough to justify any cost
  3. The CI means 95% of patients will have a personal rate ratio between 0.80 and 0.99
  4. Because the CI is close to 1.0, the result is automatically not statistically significant

Explanation: This question tests confidence intervals in asthma studies. The key parameter is the 95% CI (0.80 to 0.99) for exacerbation rate ratio. Choice A is the best because it is below 1.0, indicating significance. Choice B assumes cost justification; choice C misapplies to individuals; choice D dismisses due to proximity to 1.0. Exclusion of 1.0 confirms reduction. Clinically, assess against costs ($3,200 vs $2,600 annually).

Question 2

A budget impact model evaluated formulary addition of a new long-acting injectable antipsychotic for schizophrenia in a Medicaid plan with 100,000 members. Eligible patients were 250 (mean age 36 years; 38% female), with 40% uptake. Pharmacy spending increased by $800,000 annually, and psychiatric hospitalizations decreased by 25 per year (average cost $18,000 each). What does the budget impact model suggest for the healthcare system over 1 year?

  1. Net savings of 350,000becauseavoidedhospitalizationcosts(350,000 because avoided hospitalization costs (450,000) exceed added pharmacy costs ($800,000)
  2. Net increase of 350,000becauseaddedpharmacycosts(350,000 because added pharmacy costs (800,000) exceed avoided hospitalization costs ($450,000) (correct answer)
  3. Net savings of $800,000 because hospitalizations decreased
  4. No budget impact because schizophrenia outcomes cannot be monetized

Explanation: This question examines budget impact for antipsychotic addition. The key parameter is the net increase from $800,000 pharmacy costs exceeding $450,000 avoided hospitalizations. Choice B is the best, accurately yielding $350,000 net increase. Choice A reverses to savings; choice C overstates savings; choice D dismisses modeling validity. Budget impact quantifies fiscal effects. Frameworks should include sensitivity analyses for uptake and cost variables.

Question 3

A comparative trial randomized 1,100 patients (mean age 65 years; 44% female) with chronic coronary syndrome to Drug W vs placebo for 18 months. Myocardial infarction occurred in 4.8% vs 6.0% (absolute difference −1.2%; 95% CI −2.6% to 0.2%; p = 0.09). Drug W costs $1,200 per year. What does the p-value indicate about the study results?

  1. The results are statistically significant because p = 0.09 is less than 0.10
  2. If there were truly no difference, there is about a 9% probability of observing a difference at least this large by chance; this is not statistically significant at the 0.05 level (correct answer)
  3. There is a 91% probability Drug W prevents myocardial infarction
  4. The p-value proves Drug W is not clinically useful

Explanation: This question tests p-value meaning in coronary syndrome trials. The key parameter is p=0.09 for myocardial infarction difference. Choice B is the best, correctly interpreting under null and noting non-significance at 0.05. Choice A wrongly deems significant at 0.10; choice C misstates as probability of prevention; choice D overinterprets as proving no utility. p=0.09 >0.05 lacks significance. Clinically, evaluate trends with costs ($1,200 per year) for potential value.

Question 4

A cost-effectiveness analysis compared two smoking cessation strategies in adults (mean age 46 years; 51% female) with COPD: Strategy 1 (varenicline + counseling) vs Strategy 2 (nicotine patch + counseling). Over 1 year, Strategy 1 cost $820 and produced 0.78 QALYs; Strategy 2 cost $620 and produced 0.77 QALYs. Which treatment is most cost-effective at a willingness-to-pay threshold of $50,000 per QALY?

  1. Strategy 2, because it has lower cost and only slightly fewer QALYs, so it is always preferred
  2. Strategy 1, because the incremental cost-effectiveness ratio is $20,000 per QALY and is below $50,000 per QALY (correct answer)
  3. Strategy 2, because the incremental cost-effectiveness ratio is $200,000 per QALY
  4. Strategy 1, because any QALY gain makes a therapy automatically cost-saving

Explanation: This question assesses cost-effectiveness in smoking cessation. The key parameter is the ICER of $20,000 per QALY for Strategy 1 versus 2. Choice B is the best because it falls below $50,000 per QALY. Choice A ignores ICER; choice C miscalculates ICER; choice D assumes automatic cost-saving. The ICER supports added value. Decision frameworks prioritize strategies with ICERs under thresholds for public health interventions.

Question 5

A meta-analysis pooled 8 randomized trials (total n = 6,200; mean age 66 years; 41% female) comparing SGLT2 inhibitor therapy vs placebo in patients with heart failure with reduced ejection fraction, including those with and without diabetes. The pooled effect on heart failure hospitalization was relative risk 0.78 (95% CI 0.70 to 0.86; p < 0.001). A payer analysis estimated that avoided hospitalizations would save $1,200 per patient-year, while drug acquisition costs were $4,000 per patient-year. What is the primary conclusion from the meta-analysis?

  1. SGLT2 inhibitors significantly reduce heart failure hospitalizations compared with placebo (correct answer)
  2. SGLT2 inhibitors have no effect because the relative risk is close to 1.0
  3. SGLT2 inhibitors increase hospitalizations because p < 0.001 indicates harm
  4. The results are not statistically significant because the confidence interval includes 0

Explanation: This question tests the interpretation of meta-analysis results in heart failure therapy. The key parameter is the pooled relative risk of 0.78 (95% CI 0.70 to 0.86; p < 0.001) for heart failure hospitalizations. Choice A is the best conclusion because the relative risk below 1.0 and confidence interval excluding 1.0 indicate a significant reduction. Choice B is incorrect as the relative risk is not close to 1.0; choice C misinterprets p < 0.001 as harm; choice D wrongly states the interval includes 0, but for relative risk, significance is based on excluding 1.0. A p-value less than 0.001 strongly supports the treatment effect. Clinically, weigh efficacy against costs like $4,000 per patient-year when considering adoption.

Question 6

A meta-analysis pooled 6 trials (n = 4,100; mean age 50 years; 64% female) comparing an SSRI vs placebo for generalized anxiety disorder. The pooled response odds ratio was 1.40 (95% CI 1.15 to 1.70; p = 0.001). What is the primary conclusion from the meta-analysis?

  1. SSRIs significantly improve response compared with placebo (correct answer)
  2. SSRIs do not improve response because the confidence interval includes 1.0
  3. SSRIs worsen anxiety because the odds ratio is greater than 1.0
  4. The result is not statistically significant because p = 0.001 is greater than 0.0001

Explanation: This question evaluates meta-analysis on SSRIs for anxiety. The key parameter is the odds ratio of 1.40 (95% CI 1.15 to 1.70; p=0.001). Choice A is the best because the CI excludes 1.0, indicating significance. Choice B notes inclusion of 1.0 incorrectly; choice C misinterprets as worsening; choice D dismisses significance. Exclusion of 1.0 supports efficacy. Clinically, integrate with side effects for treatment decisions.

Question 7

A meta-analysis pooled 10 studies (n = 9,800; mean age 56 years; 50% female) evaluating pharmacist-led medication therapy management (MTM) vs usual care in patients with uncontrolled hypertension. The pooled mean systolic blood pressure reduction was −4.5 mmHg (95% CI −6.0 to −3.0; p < 0.001). MTM cost $120 per patient-year to deliver and reduced cardiovascular-related hospitalizations by 0.01 per patient-year (estimated $15,000 per hospitalization). What is the primary conclusion from the meta-analysis?

  1. MTM significantly lowers systolic blood pressure compared with usual care (correct answer)
  2. MTM does not lower blood pressure because the confidence interval includes 0
  3. MTM increases blood pressure because p < 0.001 indicates harm
  4. MTM is not effective because the reduction is only 4.5 mmHg, which cannot be statistically significant

Explanation: This question evaluates meta-analysis on MTM in hypertension. The key parameter is the mean reduction of −4.5 mmHg (95% CI −6.0 to −3.0; p<0.001). Choice A is the best because the CI excludes 0, indicating significance. Choice B notes inclusion of 0 incorrectly; choice C misinterprets p as harm; choice D dismisses clinical relevance. Exclusion of 0 confirms effect. Clinically, weigh delivery costs ($120 per patient-year) against hospitalization reductions.

Question 8

A cost-effectiveness analysis compared a new oral multiple sclerosis therapy (Drug U) vs an injectable (Drug V) in 2,000 adults (mean age 39 years; 72% female). Over 5 years, Drug U yielded 3.90 QALYs at $310,000, while Drug V yielded 3.80 QALYs at $290,000. Which treatment is most cost-effective at a willingness-to-pay threshold of $150,000 per QALY?

  1. Drug V, because it has a lower total cost and therefore must be the most cost-effective
  2. Drug U, because its incremental cost-effectiveness ratio is $200,000 per QALY and is below $150,000 per QALY
  3. Drug V, because Drug U's incremental cost-effectiveness ratio is $200,000 per QALY, which exceeds $150,000 per QALY (correct answer)
  4. Drug U, because having higher QALYs always justifies higher costs

Explanation: This question assesses cost-effectiveness in multiple sclerosis therapy. The key parameter is the ICER of $200,000 per QALY for Drug U versus V. Choice C is the best because the ICER exceeds $150,000 per QALY, favoring V. Choice A prioritizes cost without QALYs; choice B misstates the ICER as below threshold; choice D ignores ICER evaluation. The ICER highlights poor value for small QALY gain. Use thresholds to balance efficacy and affordability in chronic disease management.

Question 9

A cost-effectiveness study compared an oral hepatitis C regimen (Regimen P) vs an older regimen (Regimen Q) in 1,200 adults (mean age 52 years; 40% female) with compensated cirrhosis. Sustained virologic response was 95% with P vs 90% with Q (p = 0.03). Total treatment cost was $24,000 for P vs $18,000 for Q, and the model estimated lifetime QALYs of 14.6 (P) vs 14.4 (Q). Which treatment is most cost-effective at a willingness-to-pay threshold of $50,000 per QALY?

  1. Regimen Q, because it is less expensive and p = 0.03 is not clinically important
  2. Regimen P, because its incremental cost-effectiveness ratio is $30,000 per QALY and is below $50,000 per QALY (correct answer)
  3. Regimen Q, because the incremental cost-effectiveness ratio is $3,000 per QALY
  4. Regimen P, because a statistically significant p-value always means the therapy is cost-saving

Explanation: This question assesses cost-effectiveness in hepatitis C treatment. The key parameter is the ICER of $30,000 per QALY for Regimen P versus Q. Choice B is the best because the ICER is below the $50,000 per QALY threshold, favoring P. Choice A dismisses statistical significance without ICER context; choice C misattributes the ICER to Q; choice D wrongly links significance to cost-saving. The ICER reflects value from higher sustained virologic response. Use willingness-to-pay thresholds to determine if incremental benefits justify costs in resource-limited settings.

Question 10

In a comparative effectiveness trial, 420 adults (mean age 62 years; 52% female) with type 2 diabetes and established cardiovascular disease were randomized to Drug A vs Drug B for 24 weeks. The primary outcome (hemoglobin A1c reduction) was −1.1% with Drug A vs −0.9% with Drug B (mean difference −0.2%, 95% CI −0.35 to −0.05; p = 0.01). A cost analysis estimated total 24-week medication costs of $2,400 (Drug A) vs $1,800 (Drug B). What does the p-value indicate about the study results?

  1. There is a 1% chance that Drug A is clinically better than Drug B
  2. If there were truly no difference between Drug A and Drug B, there is about a 1% probability of observing a difference at least this large due to random chance (correct answer)
  3. Drug A will reduce hemoglobin A1c by 1.1% in 99% of patients
  4. The 95% confidence interval means there is a 95% probability the true difference is exactly −0.2%

Explanation: This question tests the interpretation of p-values in clinical trials. The key parameter is the p-value of 0.01 for the mean difference in hemoglobin A1c reduction. Choice B is the best interpretation because it correctly describes the p-value as the probability of observing the data (or more extreme) assuming the null hypothesis of no difference is true. Choice A is incorrect because the p-value does not represent the probability that one drug is clinically better; choice C misinterprets the result as applying to individual patients rather than the study population; choice D wrongly states that the confidence interval gives the probability of the true difference being exactly -0.2%. A p-value less than 0.05 indicates statistical significance, suggesting the observed difference is unlikely due to chance alone. In clinical decision-making, combine p-values with effect sizes and confidence intervals to assess practical importance.

Question 11

In a trial of 800 patients (mean age 71 years; 51% female) with osteoporosis, Drug R reduced hip fractures compared with placebo: 2.0% vs 3.0% over 2 years (relative risk 0.67; p = 0.04). The absolute risk reduction was 1.0%. Drug R costs $900 per year, and a hip fracture hospitalization was estimated at $25,000. What does the p-value indicate about the study results?

  1. There is a 4% chance that Drug R has no effect on hip fractures
  2. If Drug R truly had no effect, there is about a 4% probability of observing a difference at least this large by chance (correct answer)
  3. Drug R prevents hip fractures in 96% of patients
  4. The p-value proves Drug R is clinically meaningful and cost-saving

Explanation: This question tests p-value interpretation in osteoporosis trials. The key parameter is the p-value of 0.04 for hip fracture reduction. Choice B is the best as it accurately defines the p-value under the null hypothesis. Choice A misstates it as the probability of no effect; choice C incorrectly applies to individual efficacy; choice D conflates significance with clinical and economic outcomes. A p=0.04 <0.05 indicates statistical significance. Clinically, pair p-values with absolute risk reduction (1.0%) to evaluate number needed to treat against costs like $900 per year.

Question 12

A meta-analysis of 12 trials (n = 18,500; mean age 63 years; 47% female) evaluated a high-intensity statin vs moderate-intensity statin for major cardiovascular events. The pooled hazard ratio was 0.92 (95% CI 0.84 to 1.01; p = 0.07). Annual medication costs were $120 (moderate) vs $240 (high). What is the primary conclusion from the meta-analysis?

  1. High-intensity statin significantly reduces major cardiovascular events compared with moderate-intensity statin
  2. The pooled result is not statistically significant at the 0.05 level because the 95% CI includes 1.0 (correct answer)
  3. Moderate-intensity statin is harmful because the hazard ratio is less than 1.0
  4. The p-value of 0.07 proves there is no possible benefit from high-intensity statins

Explanation: This question evaluates meta-analysis conclusions on statin intensity. The key parameter is the pooled hazard ratio of 0.92 (95% CI 0.84 to 1.01; p=0.07). Choice B is the best because the CI includes 1.0 and p>0.05, indicating no statistical significance. Choice A claims significance without support; choice C misinterprets HR<1.0 as harm for moderate-intensity; choice D overstates p=0.07 as proving no benefit. The values suggest a potential but unconfirmed reduction. In practice, consider non-significant trends alongside costs ($240 vs $120 annually) for individualized decisions.

Question 13

A budget impact model assessed adding a new migraine preventive injection for a plan with 200,000 members. Eligible patients were estimated at 1,000 (mean age 44 years; 78% female), with 20% uptake in year 1. The drug would add $1,800,000 in pharmacy costs, while reducing emergency department visits by 300 annually (average cost $900 each). What does the budget impact model suggest for the healthcare system over 1 year?

  1. Net increase of 1,530,000becauseaddedpharmacycosts(1,530,000 because added pharmacy costs (1,800,000) exceed avoided emergency department costs ($270,000) (correct answer)
  2. Net savings of $1,530,000 because avoided emergency department costs exceed drug costs
  3. No budget impact because only clinical outcomes, not costs, should be included
  4. Net savings of $270,000 because any reduction in emergency department visits offsets all drug costs

Explanation: This question examines budget impact for migraine preventive therapy. The key parameter is the net impact from $1,800,000 added pharmacy costs and $270,000 avoided emergency department costs. Choice A is the best, calculating a net increase of $1,530,000 accurately. Choice B reverses the net calculation; choice C ignores cost integration; choice D assumes full offset unrealistically. Budget models forecast payer financial burden. Decision frameworks should project multi-year impacts to assess long-term sustainability.

Question 14

A comparative safety study in 2,400 patients (mean age 60 years; 45% female) with osteoarthritis compared NSAID AA vs NSAID BB for gastrointestinal bleeding over 6 months. Bleeding occurred in 1.8% (AA) vs 1.2% (BB), with relative risk 1.50 (95% CI 0.95 to 2.37; p = 0.08). What does the p-value indicate about the study results?

  1. The study proves NSAID AA causes gastrointestinal bleeding
  2. If there were truly no difference in bleeding risk, there is about an 8% probability of observing a difference at least this large by chance (correct answer)
  3. There is an 8% probability that the relative risk is between 0.95 and 2.37
  4. Because p = 0.08, the result is statistically significant at the 0.05 level

Explanation: This question tests p-value in NSAID safety studies. The key parameter is p=0.08 for relative risk of bleeding. Choice B is the best, accurately defining under null. Choice A claims causation; choice C misinterprets as probability for interval; choice D deems significant incorrectly. p=0.08 >0.05 lacks significance. Clinically, non-significant risks inform monitoring despite trends.

Question 15

A comparative trial enrolled 300 patients (mean age 59 years; 60% female) with rheumatoid arthritis on background methotrexate to receive Biologic M or Biologic N for 16 weeks. Clinical response occurred in 64% vs 55%, respectively (absolute difference 9%; 95% CI −2% to 20%; p = 0.11). Annual drug costs were $38,000 (M) vs $34,000 (N). How do the confidence intervals affect the interpretation of the study?

  1. Because the 95% CI includes 0, the difference in response is not statistically significant at the 0.05 level (correct answer)
  2. Because the CI includes negative values, Biologic M is proven inferior to Biologic N
  3. The CI means 95% of patients had response differences between −2% and 20%
  4. The CI confirms a clinically meaningful benefit because the point estimate is 9%

Explanation: This question evaluates confidence interval interpretation in comparative trials. The key parameter is the 95% confidence interval (−2% to 20%) for the absolute difference in clinical response. Choice A is the best because the interval includes 0, indicating no statistically significant difference at the 0.05 level. Choice B is incorrect as negative values do not prove inferiority; choice C misapplies the interval to individual patients; choice D assumes clinical meaningfulness solely from the point estimate. The interval's inclusion of 0 aligns with p=0.11 >0.05. Clinically, non-significant results suggest considering costs, like $38,000 vs $34,000 annually, in treatment selection.

Question 16

A pharmacoeconomic analysis compared a new long-acting insulin (Insulin X) to standard basal insulin in 1,000 patients (median age 58 years; 49% female) with type 2 diabetes and chronic kidney disease stage 3. Over 1 year, severe hypoglycemia occurred in 6% with Insulin X vs 9% with standard insulin (relative risk 0.67; 95% CI 0.48 to 0.94; p = 0.02). Annual drug costs were $3,600 (Insulin X) vs $2,400 (standard), and each severe hypoglycemia event was estimated to cost $4,000 in medical care. How do the confidence intervals affect the interpretation of the study?

  1. Because the 95% CI does not include 1.0, the reduction in severe hypoglycemia with Insulin X is statistically significant (correct answer)
  2. Because the 95% CI is below 1.0, Insulin X is guaranteed to be cost-saving in every health system
  3. The 95% CI means 95% of patients will have a relative risk between 0.48 and 0.94
  4. The CI indicates the study was underpowered because p = 0.02 is greater than 0.01

Explanation: This question evaluates the interpretation of confidence intervals in pharmacoeconomic analyses. The key parameter is the 95% confidence interval (0.48 to 0.94) for the relative risk of severe hypoglycemia. Choice A is the best conclusion because the interval does not include 1.0, indicating a statistically significant reduction at the 0.05 level. Choice B is incorrect as it overstates cost savings as guaranteed across all systems; choice C misapplies the confidence interval to individual patients rather than the population parameter; choice D wrongly interprets p=0.02 as evidence of underpowering. The confidence interval's exclusion of 1.0 supports rejecting the null hypothesis of no difference. When assessing clinical significance, consider both statistical results and economic factors like cost per event avoided.

Question 17

A budget impact model for a new oral COVID-19 antiviral evaluated a health plan with 1,000,000 members. In year 1, 5,000 high-risk patients (mean age 69 years; 52% female; 30% with chronic kidney disease) were expected to be treated. Drug cost was $530 per course, and hospitalization was reduced by 1.5 percentage points (from 6.0% to 4.5%); each COVID-19 hospitalization cost $20,000. What does the budget impact model suggest for the healthcare system over 1 year?

  1. Net savings of $235,000 because avoided hospitalizations (75 × $20,000 = $1,500,000) exceed drug costs (5,000 × $530 = $2,650,000)
  2. Net increase of 1,150,000becausedrugcosts(1,150,000 because drug costs (2,650,000) exceed avoided hospitalization costs ($1,500,000) (correct answer)
  3. Net savings of $1,150,000 because drug costs should be subtracted from hospitalization costs in the opposite direction
  4. No budget impact because percentage-point reductions cannot be converted to events

Explanation: This question examines budget impact for COVID-19 antiviral. The key parameter is net increase from $2,650,000 drug costs exceeding $1,500,000 avoided hospitalizations. Choice B is the best, calculating $1,150,000 increase accurately. Choice A uses wrong numbers; choice C reverses calculation; choice D denies conversion. Net increase informs budgeting. Frameworks include high-risk targeting to optimize impact.

Question 18

A cost-effectiveness analysis compared two influenza vaccination strategies for adults aged 65 years and older (mean age 72 years; 55% female): high-dose vaccine vs standard-dose vaccine. Over one season, high-dose vaccine cost $62 and produced 0.8450 QALYs; standard-dose cost $32 and produced 0.8445 QALYs. Which treatment is most cost-effective at a willingness-to-pay threshold of $100,000 per QALY?

  1. High-dose vaccine, because the incremental cost-effectiveness ratio is $60,000 per QALY and is below $100,000 per QALY (correct answer)
  2. Standard-dose vaccine, because any strategy with lower cost is always most cost-effective
  3. High-dose vaccine, because the incremental cost-effectiveness ratio is $600,000 per QALY and is below $100,000 per QALY
  4. Standard-dose vaccine, because the incremental cost-effectiveness ratio is $6,000 per QALY

Explanation: This question assesses cost-effectiveness in influenza vaccination. The key parameter is the ICER of $60,000 per QALY for high-dose versus standard. Choice A is the best because it is below $100,000 per QALY. Choice B prioritizes cost alone; choice C miscalculates ICER; choice D attributes wrong ICER. The ICER justifies added efficacy. Use seasonal models to guide elderly vaccination policies.

Question 19

A comparative study in 500 adults (mean age 57 years; 53% male) with hypertension compared Drug S vs Drug T. Blood pressure control at 12 weeks was 72% vs 70% (absolute difference 2%; 95% CI −4% to 8%; p = 0.52). Monthly costs were $40 (S) vs $10 (T). How do the confidence intervals affect the interpretation of the study?

  1. The CI suggests the true difference could favor either drug, so a statistically significant difference was not demonstrated (correct answer)
  2. The CI proves Drug S is superior because the point estimate is positive
  3. The CI means there is a 95% probability Drug S will control blood pressure in 72% of patients
  4. Because the CI includes 0, Drug T must be clinically inferior

Explanation: This question tests confidence interval effects in hypertension studies. The key parameter is the 95% CI (−4% to 8%) for blood pressure control difference. Choice A is the best because the interval includes 0, showing no significant difference (p=0.52>0.05). Choice B assumes superiority from point estimate alone; choice C misinterprets as probability for individuals; choice D wrongly infers inferiority. Inclusion of 0 suggests results could favor either drug. Clinically, non-significant findings emphasize cost differences ($40 vs $10 monthly) in therapy choice.

Question 20

A budget impact model evaluated adding a new inhaled triple therapy for COPD to a health plan with 50,000 covered lives. The eligible population was estimated at 600 patients (mean age 68 years; 55% male; frequent exacerbators). The model projected that 30% would switch to triple therapy, increasing pharmacy costs by $540,000 annually, while reducing COPD-related hospitalizations by 18 events per year (average cost $12,000 each). What does the budget impact model suggest for the healthcare system over 1 year?

  1. Net savings of 324,000becauseavoidedhospitalizations(324,000 because avoided hospitalizations (216,000) exceed added pharmacy costs ($540,000)
  2. Net increase of 324,000becauseaddedpharmacycosts(324,000 because added pharmacy costs (540,000) exceed avoided hospitalization costs ($216,000) (correct answer)
  3. No budget impact because clinical outcomes and costs cannot be compared in the same model
  4. Net savings of $540,000 because hospitalization reductions eliminate all drug costs

Explanation: This question examines budget impact modeling for COPD therapy addition. The key parameter is the net financial impact from increased pharmacy costs of $540,000 and avoided hospitalization costs of $216,000. Choice B is the best as it correctly calculates a net increase of $324,000, reflecting higher overall costs. Choice A reverses the net impact direction; choice C ignores that models integrate outcomes and costs; choice D overstates savings by assuming total offset. Budget impact assesses short-term financial effects on a payer's budget. In decision frameworks, consider if clinical benefits justify net costs beyond one year.