The present study had several strengths, the first of which was the sample on which data were collected. Participants were actual obese patients enrolled in a university-based weight loss program and, therefore, were very motivated to lose weight. This is the very group of individuals for whom questions of risk tolerance are the most pertinent and the population to whom results would be generalized. Second, the questionnaire asked risk tolerance levels for mortality and SAEs, rather than focusing on just one. Because weight loss treatments could have differential effects on mortality and occurrence of SAEs, it is valuable to have separate ratings of risk tolerance for both. Third, because no prior study has addressed this question, these findings provide the first data to address a topic of major public health significance especially given the interest in the development of new anti-obesity agents. Also, our results are consonant with those of a similar recent study23
that found that most patients undergoing obesity surgery were willing to assume only very small risks of death, with probabilities judged to be tolerable of a similar order of magnitude to those selected by our participants.
In the article by Christensen et al., 20
serious adverse events occurred more frequently in the rimonabant group (5.9%) compared to the placebo groups (4.2%). This was a significant increase in the odds of a serious adverse event = 1.4 (p=0.03). This is about the magnitude of increased risk that has been reported for increase in the odds of an MI with Vioxx.24
If we were to design a trial to study this risk prospectively, a two group chi-square test with a 0.05 two-sided significance level with 80% power to detect this difference between the rimonabant Group SAE proportion of 0.059 and the placebo Group SAE proportion of 0.042 (odds ratio of 1.43) would require a sample size in each group of 2604 or a total of 5208 patients with evaluable results unadjusted for dropouts or noncompliance.
Numbers needed to treat (NNT) are useful quantities to enable clinicians to have some idea of the importance of differences in outcomes that can be attributed to the improvement in therapy. The number needed to treat is the number of patients who would have to undergo the therapy to yield one additional person with a positive benefit. Similarly numbers needed to harm (NNH) are the number of patients treated that would yield one additional person with a serious adverse event over the comparator treatment. When different treatments are compared, the NNTs may not be comparable. NNT is computed by taking the inverse of the absolute risk reduction or the inverse of the absolute difference in the proportion of events. In the meta analysis by Christensen et al., the NNH would be 1/(.059−.042) = 1/(.017) = 58.8 or 59. That is for every 59 patients treated with rimonabant, 1 additional SAE would occur over a patient treated with a placebo.
It should be noted that NNTs and NNHs are useful for comparisons when the trials are very similar, but can be misleading when the event rates are very different, such as can happen when very different patient populations are studied. For example, if the SAE rates in a very healthy population were 0.016 versus 0.008 for the rimonabant versus control, the relative risk increase would be 2 and the NNH would be 1/(0.016−0.008) = 1/0.008 = 125. If the rates were from a population of sicker patients, such that the SAE rates were 0.06 and 0.03 respectively, the NNH would be 1/(0.06−0.03) = 1/0.03 = 33.3 or 34. Thus, while the relative risk is still 2 in both cases in this example, the number needed to harm requires only about a fourth of the patients before we would see one additional case. Thus, the NNT and NNH are solely functions of the absolute difference between the rates and have little relationship to risk reduction or increase in risk.
A limitation of the study includes the use of a sample that was from a single site from the northeast. Thus, generalizability of results needs to be established in larger samples from other geographic regions. We also note that the proportion of men in our sample was low. That being said, data show that most (roughly 80%) individuals who participate in obesity treatment trials are women. For example, Brennan et al.25
reviewed 5 studies with 73–84% female in RCTs testing Sibutramine, Muls et al.26
had 80% females, and McMillan-Price et al.27
conducted a dietary RCT for weight loss with 75% females. Thus, while our sample may not be representative of the general population or even the obese population overall in terms of gender, it is representative of the population to which we wish to generalize, namely obese individuals who enter RCTs. Hence the low proportion of men in the study may be considered normative. Given that this was the first study to address the problem of obese patients’ perception of risk and how much weight they might want to lose considering the risk associated with the weight loss, this seems an appropriate sample. Future research should study larger samples of men to obtain better estimates for men. Finally, our findings may not pertain to perceptions of tolerable risks for childhood obesity treatments, which may be even lower for many individuals.
A second concern is that some participants gave responses that seemed counterintuitive to the investigators which suggested that our questionnaire may have tapped constructs other than pure risk tolerance or that our preconceived perceptions of risk tolerance are not in accordance with risk perceptions for many people. One study indicated that participants may misunderstand risks due to confusion with probabilities and stated that subjects actually perceiving a risk of 1/200 as more likely than one of 1/100.28
This suggests the possibility that many subjects simply do not understand risk quantification well.
Alternatively, these seemingly counterintuitive results may be valid indicators of subjects’ perceptions. Clinical staff had communicated to subjects that they should only expect modest weight losses during the RCTs. Therefore, the 5 and 10% amounts of weight loss are reasonable amounts to focus on for this study group. Others have stated that the 5 and 10% weight losses are reasonable targets when measuring the effects of anti-obesity pharmaceuticals.21
Our subjects were, for the most part, below BMI 40 which is a commonly used cut-off for bariatric surgery.29
Hence, to expect this study group to anticipate and realistically entertain a 20–50% weight loss may not have been reasonable. Indeed, Fabricatore et al.30
recently reported that “Respondents' weight loss expectations for their upcoming attempt (8.0% reduction in initial weight) were significantly more modest than their goals for that attempt (16.8%), and smaller than the losses that they expected (12.0%), and achieved (8.9%) in their most recent past attempt… Results suggest that overweight and obese individuals can select realistic weight loss expectations that are more modest than their ideal goals.” Thus, while obese people may desire large weight losses, in most cases, they do not realistically expect them. With this in mind, the initially counterintuitive results may make sense from a perspective of how individuals determine how much they would be willing to pay for a benefit like weight loss (i.e., an inquiry into subjective valuation as practiced by economists). Individuals may make this type of determination based on the desirability of the benefit as well as the plausibility of its attainment. Although our questionnaire implicitly asked subjects to assume that each weight loss level was attainable, subjects may have been unable or unwilling to engage in such a suspension of disbelief. In turn, this may have caused them to discount the value of the larger weight losses. With these large weight losses discounted, it is then rational to be willing to pay much less (i.e., assume less risk) for the weight losses. In other words, the subjects may have truly been willing to pay less risk to lose more weight because they did not think losing large amounts of weight was realistic.
Implications and Directions for Future Research
The implications of these results are clear. They suggest that the maximum added risks that most participants are willing to tolerate in exchange for realistic weight losses are far smaller than the added risks that can be detected in most extant obesity RCTs. This suggests that either patients do not have realistic expectations regarding the safety assessments that current obesity RCTs can offer, or patients are not really expecting obesity RCTs to rule out risks they find excessive. If the latter, then there may be no need for action. However, if the former is true, it may suggest that patients do not have a good understanding of risk and what current obesity RCTs are capable of doing and therefore may not be providing truly informed consent. The possibility that patients do not have realistic expectations or a clear understanding of risks and the safety assessments that current obesity RCTs can offer is made all the more plausible by the odd pattern of results obtained for some participants when they stated that they were counterintuitively willing to assume larger risks in exchange for smaller weight losses. If this is true, a better education campaign for participants in RCTs involving investigational drugs and perhaps patients taking marketed drugs may be needed. Subsequently, participants may need to be willing to accept greater uncertainty once risks they judge to be meaningful have been ruled out or RCT sizes may need to be increased. Finally, future research should attempt to develop better ways of asking patients in obesity RCTs about the risks they find tolerable in order to replicate and extend this research.