Jørgen Nexøe

Number needed to treat: easily understood and intuitively meaningful? Theoretical considerations and a randomized trial

Graphic representation was used to explore to what extent the number needed to treat (NNT) conveys the appropriate notion of benefit for the individual patient in interventions aimed at delaying adverse events. A sample of the Danish population (n = 675) was interviewed face to face, and asked whether they would consent to a hypothetical drug that reduces the risk of heart attack. The benefit of the drug was expressed in terms of NNT and was randomly set at 10, 25, 50, 100, 200, and 400. NNT does not convey information on the proportion of patients being helped by an intervention or the size of the delay of the adverse event intended to be prevented. The proportion of people consenting to the hypothetical drug was about 80%, irrespective of NNT, and some of those who rejected the drug misinterpreted the meaning of NNT. Lay people may have difficulties in understanding the meaning of NNT, and clinicians may do well to use the NNT with caution until more is known about how patients comprehend it.

Laypersons' understanding of relative risk reductions: randomised cross-sectional study.

BackgroundDespite increasing recognition of the importance of involving patients in decisions on preventive healthcare interventions, little is known about how well patients understand and utilise information provided on the relative benefits from these interventions. The aim of this study was to explore whether lay people can discriminate between preventive interventions when effectiveness is presented in terms of relative risk reduction (RRR), and whether such discrimination is influenced by presentation of baseline risk.MethodsThe study was a randomised cross-sectional interview survey of a representative sample (n = 1,519) of lay people with mean age 59 (range 40–98) years in Denmark. In addition to demographic information, respondents were asked to consider a hypothetical drug treatment to prevent heart attack. Its effectiveness was randomly presented as RRR of 10, 20, 30, 40, 50 or 60 percent, and half of the respondents were presented with quantitative information on the baseline risk of heart attack. The respondents had also been asked whether they were diagnosed with hypercholesterolemia or had experienced a heart attack.ResultsIn total, 873 (58%) of the respondents consented to the hypothetical treatment. While 49% accepted the treatment when RRR = 10%, the acceptance rate was 58–60% for RRR>10. There was no significant difference in acceptance rates across respondents irrespective of whether they had been presented with quantitative information on baseline risk or not.ConclusionIn this study, lay peoples decisions about therapy were only slightly influenced by the magnitude of the effect when it was presented in terms of RRR. The results may indicate that lay people have difficulties in discriminating between levels of effectiveness when they are presented in terms of RRR.

Can postponement of an adverse outcome be used to present risk reductions to a lay audience?: A population survey

BackgroundFor shared decision making doctors need to communicate the effectiveness of therapies such that patients can understand it and discriminate between small and large effects. Previous research indicates that patients have difficulties in understanding risk measures. This study aimed to test the hypothesis that lay people may be able to discriminate between therapies when their effectiveness is expressed in terms of postponement of an adverse disease event.MethodsIn 2004 a random sample of 1,367 non-institutionalized Danes aged 40+ was interviewed in person. The participants were asked for demographic information and asked to consider a hypothetical preventive drug treatment. The respondents were randomized to the magnitude of treatment effectiveness (heart attack postponement of 1 month, 6 months, 12 months, 2 years, 4 years and 8 years) and subsequently asked whether they would take such a therapy. They were also asked whether they had hypercholesterolemia or had experienced a heart attack.ResultsIn total 58% of the respondents consented to the hypothetical treatment. The proportions accepting treatment were 39%, 52%, 56%, 64%, 67% and 73% when postponement was 1 month, 6 months, 12 months, 2 years, 4 years and 8 years respectively. Participants who thought that the effectiveness information was difficult to understand, were less likely to consent to therapy (p = 0.004).ConclusionLay people can discriminate between levels of treatment effectiveness when they are presented in terms of postponement of an adverse event. The results indicate that such postponement is a comprehensible measure of effectiveness.

How Do Individuals Apply Risk Information When Choosing Among Health Care Interventions

A sample of 3,201 Danes was subjected to personal interviews in which they were asked to state their preferences for risk-reducing health care interventions based on information on absolute risk reduction (ARR) and relative risk reduction (RRR). The aim of the study was to measure the relative weighting of different types of risk information under various circumstances. The effect of presenting questions, and of explicitly formulating RRR, was analyzed. A preference for increases in RRR was demonstrated. There was a stronger inclination to choose the intervention that offered the highest RRR if RRR was explicitly stated. Individuals with more than 10 years of schooling also demonstrated a preference for increased ARR, but only when facing individually framed choices. In a social choice context, preferences for RRR remained intact, but the magnitude of ARR had no impact on choices. Results imply that social framing may induce a propensity to prefer interventions that target high-risk populations. Those respondents who had received < or = 10 years of schooling demonstrated preferences for RRR but not ARR, and no impact of social framing was observed.

Perception of risk information. Similarities and differences between Danish and Polish general practitioners

Objective - The objective of the study was to gain better insight into how general practitioners (GPs) perceive risk reduction and the way this perception may be influenced by healthcare environment. Design - Questionnaires with clinical episodes were sent to Danish and Polish GPs, who were randomised into four groups, each receiving the same case story with differently phrased information about risk reduction achieved through medical treatment. The GPs were asked whether they would recommend medical treatment, knowing the case story and expected risk reduction. Subjects - Danish and Polish GPs. Results - A greater proportion of Polish GPs than Danish GPs would definitely or probably recommend treatment (93% versus 72%; p < 0.001). Both groups of doctors were more inclined to recommend treatment when the achievable benefits were presented in terms of relative risk reduction rather than absolute risk reduction or number needed to treat. Conclusion - Neither information on number needed to treat nor relative risk reduction alone provides doctors with all the information they need to recommend treatment or prevention to their patients. The present study showed that the professional handling of risk information is affected by differences produced by healthcare cultures.

Effects of Baseline Risk Information on Social and Individual Choices

This article analyzes preferences for risk reductions in the context of individual and societal decision making. The effect of information on baseline risk is analyzed in both contexts. The results indicate that if individuals are to imagine that they suffer from 1 low-risk and 1 high-risk ailment, and are offered a specified identical absolute risk reduction, a majority will ceteris paribus opt for treatment of the low-risk ailment. A different preference structure is elicited when priority questions are framed as social choices. Here, a majority will prefer to treat the high-risk group of patients. The preference reversal demonstrates the extent to which baseline risk information can influence preferences in different choice settings. It is argued that presentation of baseline risk information may induce framing effects that lead to nonoptimal resource allocations. A solution to this problem may be to not present group-specific baseline risk information when eliciting preferences.

Medication effectiveness may not be the major reason for accepting cardiovascular preventive medication: A population-based survey

BackgroundShared decision-making and patients’ choice of interventions are areas of increasing importance, not least seen in the light of the fact that chronic conditions are increasing, interventions considered important for public health, and still non-acceptance of especially risk-reducing treatments of cardiovascular diseases (CVD) is prevalent. A better understanding of patients’ medication-taking behavior is needed and may be reached by studying the reasons why people accept or decline medication recommendations. The aim of this paper was to identify factors that may influence people’s decisions and reasoning for accepting or declining a cardiovascular preventive medication offer.MethodsFrom a random sample of 4,000 people aged 40–59 years in a Danish population, 1,169 participants were asked to imagine being at increased risk of cardiovascular disease and being offered a preventive medication. After receiving ‘complete’ information about effectiveness of the medication they were asked whether they would accept medication. Finally, they were asked about reasons for the decision.ResultsA total of 725 (67%) of 1,082 participants accepted the medication offer. Even quite large effects of medication (up to 8 percentage points absolute risk reduction) had a smaller impact on acceptance to medication than personal experience with cardiovascular disease. Furthermore, increasing age of the participant and living with a partner were significantly associated with acceptance. Some 45% of the respondents accepting justified their choice as being for health reasons, and they were more likely to be women, live alone, have higher income and higher education levels. Among those who did not accept the medication offer, 56% indicated that they would rather prefer to change lifestyle.ConclusionsMedication effectiveness seems to have a moderate influence on people’s decisions to accept preventive medication, while factors such as personal experience with cardiovascular disease may have an equally strong or stronger influence, indicating that practitioners could do well to carefully identify the reasons for their patients’ treatment decisions.

Association of lipoprotein levels with mortality in subjects aged 50 + without previous diabetes or cardiovascular disease: a population-based register study

Abstract Objective. This study aimed to investigate the association of lipoprotein and triglyceride levels with all-cause mortality in a population free from diabetes and cardiovascular disease (CVD) at baseline. The European Guidelines on cardiovascular disease prevention state that in general total cholesterol (TC) should be < 5 mmol/L (190 mg/dL) and low-density lipoprotein cholesterol (LDL-C) should be < 3 mmol/L (115 mg/dL). Design. A population-based register study in the period 1999–2007 including 118 160 subjects aged 50 + without statin use at baseline. All-cause mortality was related to lipoprotein and triglyceride levels and adjusted for statin use after inclusion. Results. All-cause mortality was lower in the groups with TC or LDL-C above the recommended levels. Compared with subjects with TC < 5 mmol/L, adjusted hazard ratios for the group aged 60–70 years ranged from 0.68 (95% confidence interval (CI) 0.61–0.77) for TC 5–5.99 mmol/L to 0.67 (95% CI 0.59–0.75) for TC 6–7.99 mmol/L and 1.02 (95% CI 0.68–1.53) for TC ≥ 8 mmol/L in males and from 0.57 (95% CI 0.48–0.67) to 0.59 (95% CI 0.50–0.68) and 1.02 (95% CI: 0.77–1.37) in females. For triglycerides, ratios compared with the group < 1 mmol/L in the females aged 60–70 years ranged from 1.04 (95% CI 0.88–1.23) to 1.35 (95% CI 1.10–1.66) and 1.25 (95% CI 1.05–1.48) for triglycerides 1–1.39 mmol/L, 1.4–1.69 mmol/L, and ≥ 1.7 mmol/L, respectively. Statin treatment after inclusion provided a survival benefit. Conclusion. These associations indicate that high lipoprotein levels do not seem to be definitely harmful in the general population. However, high triglyceride levels in females are associated with decreased survival.

A competing risk approach for the European Heart SCORE model based on cause-specific and all-cause mortality.

Background: The European Heart SCORE model constitutes the basis for national guidelines for primary prevention and treatment of cardiovascular disease (CVD) in several European countries. The model estimates individuals’ 10-year CVD mortality risks from age, sex, smoking status, systolic blood pressure, and total cholesterol level. The SCORE model, however, is not mathematically consistent and does not estimate all-cause mortality. Our aim is to modify the SCORE model to allow consistent estimation of both CVD-specific and all-cause mortality. Methods: Using a competing risk approach, we first re-estimated the cause-specific risk of dying from cardiovascular disease, and secondly we incorporated non-CVD mortality. Finally, non-CVD mortality was allowed to also depend on smoking status, and not only age and sex. From the models, we estimated CVD-specific and all-cause 10-year mortality risk, and the expected residual lifetime together with corresponding expected effects of statin treatment. Results: The modified model provided CVD-specific 10-year mortality risks similar to those of the European Heart SCORE model. Incorporation of non-CVD mortality increased 10-year mortality risks, in particular for older individuals. When non-CVD mortality was assumed unaffected by smoking status, the absolute risk reduction due to statin treatment ranged from 0.0% to 3.5%, whereas the gain in expected residual lifetime ranged from 3 to 11 months. Statin effectiveness increased for non-smokers and declined for smokers, when smoking was allowed to influence non-CVD mortality. Conclusion: The modified model provides mathematically consistent estimates of mortality risk and expected residual lifetime together with expected benefits from statin treatment.

Joint and Separate Evaluation of Risk Reduction: Impact on Sensitivity to Risk Reduction Magnitude in the Context of 4 Different Risk Information Formats

Background. When people make choices, they may have multiple options presented simultaneously or, alternatively, have options presented 1 at a time. It has been shown that if decision makers have little experience with or difficulties in understanding certain attributes, these attributes will have greater impact in joint evaluations than in separate evaluations. The authors investigated the impact of separate versus joint evaluations in a health care context in which laypeople were presented with the possibility of participating in risk-reducing drug therapies. Methods. In a randomized study comprising 895 subjects aged 40 to 59 y in Odense, Denmark, subjects were randomized to receive information in terms of absolute risk reduction (ARR), relative risk reduction (RRR), number needed to treat (NNT), or prolongation of life (POL), all with respect to heart attack, and they were asked whether they would be willing to receive a specified treatment. Respondents were randomly allocated to valuing the interventions separately (either great effect or small effect) or jointly (small effect and large effect). Results. Joint evaluation reduced the propensity to accept the intervention that offered the smallest effect. Respondents were more sensitive to scale when faced with a joint evaluation for information formats ARR, RRR, and POL but not for NNT. Evaluability bias appeared to be most pronounced for POL and ARR. Conclusion. Risk information appears to be prone to evaluability bias. This suggests that numeric information on health gains is difficult to evaluate in isolation. Consequently, such information may bear too little weight in separate evaluations of risk-reducing interventions.