For NU505 Unit 4, the published ASCEND aspirin trial yields ratio and difference measures for benefit and harm, compared side by side to show which belongs in which conversation. Searches like "nu 505 unit 4 assignment example", "nu505 unit 4 sample" and "nu505 unit 4 example" land here.
Eleven Events Prevented, Nine Bleeds Caused: A Risk Measure Exercise on Aspirin for Primary Prevention in Adults With Diabetes, From the ASCEND Trial
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Purdue University Global
NU505: Clinical Epidemiology and Population Health Promotion
Unit 4 Assignment
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[Date]
Counts are from the published ASCEND trial; per-arm denominators are taken as half of the 15,480 randomized, and derived figures are the writer's.
The Trial
ASCEND randomized 15,480 adults with diabetes but no evident cardiovascular disease to aspirin 100 mg daily or matching placebo and followed them for a mean of 7.4 years (ASCEND Study Collaborative Group, 2018). The primary efficacy outcome was the first serious vascular event: myocardial infarction, stroke or transient ischemic attack, or vascular death. The primary safety outcome was the first major bleeding event. For this exercise each arm is taken as 7,740 participants.
Table 1: Benefit, Serious Vascular Events
1. Events: 658 on aspirin; 743 on placebo.
2. Risks over the follow-up: 658 divided by 7,740 equals 8.5 percent; 743 divided by 7,740 equals 9.6 percent.
3. Relative risk: 8.5 divided by 9.6 equals 0.89 by simple risks. The trial reported a rate ratio of 0.88, 95% CI 0.79 to 0.97, from its time-to-event analysis; the two agree closely.
4. Relative change: a 12 percent reduction.
5. Absolute risk reduction: 9.6 minus 8.5 equals 1.1 percentage points, about 11 events prevented per 1,000 treated over 7.4 years.
6. Number needed to treat: 1 divided by 0.011 equals about 91 people treated for 7.4 years to prevent one serious vascular event.
Table 2: Harm, Major Bleeding
1. Events: 314 on aspirin; 245 on placebo.
2. Risks: 314 divided by 7,740 equals 4.1 percent; 245 divided by 7,740 equals 3.2 percent.
3. Relative risk: 4.1 divided by 3.2 equals 1.28 by simple risks; reported rate ratio 1.29, 95% CI 1.09 to 1.52.
4. Relative change: a 29 percent increase.
5. Absolute risk increase: 0.9 percentage points, about 9 additional major bleeds per 1,000 treated over 7.4 years, most of them gastrointestinal or other bleeding outside the skull.
6. Number needed to harm: 1 divided by 0.0089 equals about 112.
Comparing Benefit and Harm
The relative measures cannot be weighed against each other directly. A 12 percent reduction and a 29 percent increase rest on different baselines: the reduction applies to a vascular event risk near 10 percent, the increase to a bleeding risk near 3 percent. Set against each other as percentages, harm looks more than twice as large as benefit; set against each other as counts, the two are close, about 11 events prevented and 9 bleeds caused per 1,000. The absolute figures are the ones that can be compared, and they show a close balance. Whether it tips one way depends on how a person values a heart attack or stroke avoided against a major bleed, most of which in this trial were not intracranial.
Table 3: The Same Relative Effect at Higher Baseline Risk
Suppose a patient's risk of a serious vascular event over the same period is 20 percent rather than 9.6 percent, and the relative effect stays at 0.88, as it tends to across risk levels.
1. Risk with aspirin: 20 times 0.88 equals 17.6 percent.
2. Absolute risk reduction: 2.4 percentage points, about 24 events prevented per 1,000.
3. Number needed to treat: about 42.
If this patient's bleeding risk is typical of the trial, about 9 additional bleeds per 1,000 still apply, and the balance now favors benefit more clearly. If the patient's bleeding risk is also higher, for example because of prior ulcer disease, the balance may not move at all.
Which Measure Belongs Where
Relative risk belongs in describing whether the drug works and how consistently, since it tends to stay stable across groups. Absolute differences and numbers needed belong in the conversation with a patient and in any decision about a population, since they carry the baseline (Celentano & Szklo, 2019). A statement that aspirin "cuts vascular events by 12 percent" is accurate and, without the bleeding figure and the counts, misleading.
Three Ways the Same Result Could Be Reported
The same trial supports three headlines, and each is literally true. "Aspirin cuts heart attacks and strokes by 12 percent in people with diabetes" uses the relative benefit alone. "Aspirin raises major bleeding by 29 percent" uses the relative harm alone. "For every 1,000 adults with diabetes who take aspirin for about seven years, about 11 avoid a serious vascular event and about 9 have a major bleed" uses both absolute figures and the time frame. Only the third lets a reader make a decision, and it is the one least often printed. A nurse counseling a patient should be ready to translate either of the first two into the third.
Link to Current Guidance
The pattern in these tables is the reason current federal guidance is cautious. Current federal advice leaves the choice to start low-dose aspirin to the individual for adults in their forties and fifties whose estimated ten-year risk reaches the task force's 10 percent threshold, and advises against starting it at 60 and older (US Preventive Services Task Force, 2022). The absolute figures from ASCEND show why: at average risk, the events prevented and the bleeds caused are of similar size, and the decision depends on the individual's own risks.
References
ASCEND Study Collaborative Group. (2018). Effects of aspirin for primary prevention in persons with diabetes mellitus. New England Journal of Medicine, 379(16), 1529-1539. https://doi.org/10.1056/NEJMoa1804988
Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier.
US Preventive Services Task Force. (2022). Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement. JAMA, 327(16), 1577-1584. https://doi.org/10.1001/jama.2022.4983
How this NU505 Unit 4 example is structured
Benefit and harm from the published ASCEND trial are computed in parallel, so the two can be read row by row, and each table runs from counts to risks to relative measures to absolute ones. That order matters: every derived figure is traceable to the counts, and the absolute measures come last because they carry the decision. The comparison section is the core. It shows that a 12 percent relative reduction and a 29 percent relative increase cannot be weighed directly, since they rest on different baselines, while about 11 events avoided and 9 bleeds added per 1,000 can. A rerun at higher baseline risk shows the relative effect staying fixed while the absolute benefit grows. The exercise then assigns each measure to its use and links the pattern to current federal task force advice on aspirin.
Get an NU505 Unit 4 example written to your instructions
Bring the trial or results table your Unit 4 exercise uses, the questions, and your rubric. Benefit and harm are then derived from counts, compared per 1,000 and assigned to the right audience. The first custom sample is on the house, written to those instructions, and arrives in 24-48h. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
NU505 Unit 4 questions, answered
Why can a relative reduction and a relative increase not be compared directly?
Because each is a percentage of a different baseline. A 16 percent drop from 4.9 percent and a 41 percent rise from 2.7 percent translate into 8 fewer events and 11 more bleeds per 1,000. The relative figures make the benefit and harm look incommensurable, while the absolute figures put them on one scale a patient can weigh.
How does baseline risk change the number needed to treat?
If the relative effect holds steady, a higher baseline risk produces a larger absolute reduction and a smaller number needed to treat. At 4.9 percent baseline the example gets 125; at 10 percent it gets about 62. That is why guidelines often tie preventive therapy to estimated risk rather than recommending it for everyone in an age group.
Is it realistic to assume bleeding risk stays the same in higher-risk patients?
Often it is not, since many factors that raise cardiovascular risk, such as age and kidney disease, also raise bleeding risk. The example flags the assumption and notes that a real decision would estimate both risks for the individual. Stating the assumption openly is what earns credit, even though the calculation itself holds bleeding constant for simplicity.