Pone.0002291 1.7

Why Are Clinicians Not Embracing the Results fromPivotal Clinical Trials in Severe Sepsis? A BayesianAnalysis 1 Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, United States of America, 2 Assistant Professor, Department of Biostatistics, College of Public Health, University of Nebraska, Omaha, Nebraska, United States of America Background: Five pivotal clinical trials (Intensive Insulin Therapy; Recombinant Human Activated Protein C [rhAPC]; Low-Tidal Volume; Low-Dose Steroid; Early Goal-Directed Therapy [EGDT]) demonstrated mortality reduction in patients withsevere sepsis and expert guidelines have recommended them to clinical practice. Yet, the adoption of these therapiesremains low among clinicians.
Objectives: We selected these five trials and asked: Question 1-What is the current probability that the new therapy is notbetter than the standard of care in my patient with severe sepsis? Question 2-What is the current probability of reducing therelative risk of death (RRR) of my patient with severe sepsis by meaningful clinical thresholds (RRR .15%; .20%; .25%)? Methods: Bayesian methodologies were applied to this study. Odds ratio (OR) was considered for Question 1, and RRR wasused for Question 2. We constructed prior distributions (enthusiastic; mild, moderate, and severe skeptic) based on variouseffective sample sizes of other relevant clinical trials (unfavorable evidence). Posterior distributions were calculated bycombining the prior distributions and the data from pivotal trials (favorable evidence).
Main Findings: Answer 1-The analysis based on mild skeptic prior shows beneficial results with the Intensive Insulin, rhAPC,and Low-Tidal Volume trials, but not with the Low-Dose Steroid and EGDT trials. All trials’ results become unacceptable bythe analyses using moderate or severe skeptic priors. Answer 2-If we aim for a RRR.15%, the mild skeptic analysis showsthat the current probability of reducing death by this clinical threshold is 88% for the Intensive Insulin, 62–65% for the Low-Tidal Volume, rhAPC, EGDT trials, and 17% for the Low-Dose Steroid trial. The moderate and severe skeptic analyses show noclinically meaningful reduction in the risk of death for all trials. If we aim for a RRR .20% or .25%, all probabilities ofbenefits become lower independent of the degree of skepticism.
Conclusions: Our clinical threshold analysis offers a new bedside tool to be directly applied to the care of patients withsevere sepsis. Our results demonstrate that the strength of evidence (statistical and clinical) is weak for all trials, particularlyfor the Low-Dose Steroid and EGDT trials. It is essential to replicate the results of each of these five clinical trials inconfirmatory studies if we want to provide patient care based on scientifically sound evidence.
Citation: Kalil AC, Sun J (2008) Why Are Clinicians Not Embracing the Results from Pivotal Clinical Trials in Severe Sepsis? A Bayesian Analysis. PLoS ONE 3(5):e2291. doi:10.1371/journal.pone.0002291 Editor: Adam J. Ratner, Columbia University, United States of America Received October 26, 2007; Accepted April 9, 2008; Published May 28, 2008 Copyright: ß 2008 Kalil, Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricteduse, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors have no support or funding to report.
Competing Interests: The authors have declared that no competing interests exist.
results and brought the prospect of improving the survival ofpatients with severe sepsis.
‘‘If we begin with certainties, we shall end in doubts; but if we begin Ten multinational medical societies sponsored a joint statement, with doubts, and are patient with them, we shall end with certainties.’’ ‘Surviving Sepsis Campaign’, in which recommendations aremade to include the results of these trials in the standard of care for patients with severe sepsis [7]. These recommendations have also More than 20 clinical trials involving over 10,000 patients have been evaluated by the Joint Commission on Accreditation of been performed in patients with sepsis and severe sepsis in the last Healthcare Organizations [8]. Despite these positive outcomes 15 years with little success in reducing mortality [1]. More and recommendations, scientists and clinicians have been either recently, five published clinical trials: Early Goal-Directed slow or resistant to adopt the results of these trials at face value in Therapy [2], Recombinant Human Activated Protein C [3], order to apply them to patient care [9–25]. Still, strong Low-Dose Steroid [4], Low-Tidal Volume-ARDS Network [5], endorsement by the medical societies is not coming without and Intensive Insulin Therapy [6] demonstrated positive outcome criticisms and opposition by the medical community [8,26]. Why is this resistance to accept statistically significant results from large probability of having a disease based on tests results without clinical trials so accentuated in the sepsis field? specifying the disease’s prevalence’’ [37]. The basic idea described We propose that the genesis for most of these issues lies in the by Bayes demonstrates that the product between the prior confounding interpretation and poor translation of these results to probability and the evidence provided by the new trial (also called the bedside, and the lack of formal analysis combining previous Bayes factor) will give us the posterior probability, which we call evidence and the current positive clinical trials. While controversy the ‘‘current probability’’ in our paper. This simple and clever is necessary for the progression of science [27], when it comes to algebraic calculation allows us to overcome the unsolvable ‘long treating a patient with severe sepsis, a clinical decision is also term hypothetical repetitions’ inherent issue of the classic method.
necessary for the betterment of this patient’s outcome.
At the same time, it gives us what we are mostly looking for in our In the following paragraphs, we argue that the best solution for daily medical practice, i.e. what is the current probability to the understanding of pivotal clinical trials in severe sepsis can only achieve the results of this pivotal trial in my patients? The potential come from a friendly reunion of classic (frequentist) and Bayesian ‘‘subjectivity’’ of these priors have made some statisticians and statistical methodologies [28–31]. The application of this more clinicians concerned about the use of this method. However, the inclusive and robust interpretation of trial results will facilitate complete exclusion of prior knowledge and evidence from the their application directly to the bedside, and will hopefully further design and interpretation of recently completed clinical trials has improve the care of our patients with severe sepsis. Moreover, this been compared to a sentencing judge who overlooks the prior ‘‘dualistic’’ approach will also empower us to better define the convictions of a habitual criminal [38]. Needless to say, the need for confirmatory trials in order to optimize the current commonly used classic methodology in current clinical trials is far from objective. For example, the models assumed, the parametersand hypothesis chosen, and the experimental designs employed [37] are typical features that incorporate much subjectivity intothe classic analysis. We agree with Berry [37] that ‘‘…silent subjectivities such as these (seen with classic methods) are The ‘‘early goal-directed therapy’’ (EGDT) trial [2] will be used dangerous in that they are difficult or impossible to make explicit.
as a practical example to describe the rationale for our By contrast, subjectivity in prior distributions (as seen with methodology. This trial aimed to compare the use of early volume Bayesian methods) is explicit and open to examination-and replacement/vasopressor use in the treatment arm against critique-by all’’. Thus, how should we best determine the priors standard of care in the control arm for patients with severe sepsis.
for this study? This so-called subjectivity is easily resolved in the The final results showed a 42% relative reduction in the risk of severe sepsis world because we have many negative clinical trials death (16% absolute risk reduction) of in-hospital mortality with a done before the current positive trials, which set the stage for the 95% confidence interval (CI) (0.13–0.62), p = 0.009. Common perfect use of Bayesian methodology. We will provide the clinician clinical interpretations are: (a) there is only a 0.9% probability of a with a realistic spectrum of prior distributions, so he/she can find false positive result (rejecting the null hypothesis when there is no the current probability of the new treatment being no better than treatment difference); (b) there is a 95% probability of the true risk the control (standard of care), and the current probability of ratio being somewhere between 0.13 and 0.62 (a reduction of 13– reducing mortality by a clinically meaningful threshold. These two 62% in the relative risk of death). These interpretations are probabilities will allow the clinician to make the best clinical incorrect due to the misunderstanding of the classic or frequentist decision for the patient with severe sepsis without being entirely (frequency based view of probability) statistical reporting used in dependent on sponsors, regulators, editors, and experts in the field.
this and most trials [32–35]. The correct interpretation of theclassic method for this trial is the following: There is a 0.9% probability that results as good as or better than the ones found in 1. What is the current probability that the new therapy is this trial (42% relative reduction in the risk of death), will be not better than the standard of care in my patient with observed among a large number of hypothetical repetitions of this The goal of the first part of our study is to assess trial under the null hypothesis of no treatment effect. In addition, the current probability that the new therapy is no better than the the CIs generated from 95% of these hypothetical trials will cover control, i.e. standard of care. We used the log-odds ratio (ln(OR)) the true mortality reduction. This rather convoluted language is of death for the new treatment group compared to the control the only possible interpretation which explicitly states that the group. We considered the new therapy to be no better than the classic method cannot provide the probabilities that clinicians are control if the ln(OR) was found to be greater than 20.05 [38,39].
seeking for. In other words, clinicians are interpreting the We then constructed various prior distributions of ln(OR) conventional p values and CIs as ‘current probabilities’, although assuming previous trials of different effective sample sizes (see the classic method alone only provides us with probabilities over a Appendix S1). The prior distributions may be based on the large number of hypothetical repetitions in the long term.
following information: Early Goal-Directed Therapy [40–47], Here is where the Bayesian methodology comes in to rhAPC [48–53], Low-Dose Steroids [54–67], Low-Tidal Volume complement the classic interpretation of clinical trials. It allows [68–74], Intensive Insulin Therapy [75–85]. Of note, some trials us to think the way most clinicians are already thinking [36]! That were performed before and others after the pivotal positive trial of is, what is the posterior or ‘current probability’ (not the probability a given therapy. This inclusive approach of all evidence available in the long term of hypothetical trial repetitions) of observing this is an important strength of the Bayesian technique, which does not outcome in a given trial or population.
require that the priors have a temporal order [32,37,86,87]. This In order to use the Bayesian methodology, a prior probability is list of studies for each therapy allows the reader to get his/her own required. The prior probability can be based on all available effective sample size by summing up the prior unfavorable evidence (i.e. biological rationale and its pre-clinical evaluation; evidence (total sample size of relevant negative clinical trials). If observational and experimental clinical data) gathered by studies believing there is no relevant previous negative data, one can other than the new trial being currently analyzed. An analogy to assume the effective sample size to be 1 [88]. This gives us the non- the diagnostic setting states that ‘‘it is not possible to find a informative prior, which is our ‘enthusiastic’ prior, since it is Table 1. Current probability of new treatment being no better than control based on mortality outcomes.
Sample Size of Unfavorable Evidence (Bayesian Priors) CURRENT PROBABILITY OF NEW TREATMENT BEING NO BETTER THAN CONTROL MILD-MODERATE SKEPTIC (Sample Size = 500) ignoring all negative sepsis trials already published. If one is publication (42%). This level of prediction can not be achieved skeptical about the effects of the new therapy based on previous phase 2 and 3 trials, observational studies, or clinical experience, The results of the five positive clinical trials [2–6] will be the effective sample size of negative evidence for the (skeptical) discussed in the context of the two probability questions described prior will be larger. Thus, the more skeptical one is based on the above. Because of the non-significant overall results of the low- prior information, the harder it is to conclude efficacy using the steroid trial for mortality [4], we will evaluate the prospectively same pivotal trial data. Based on the mortality rate and the defined ‘‘non-responders’’ sub-population. Due to the low overall required sample size to evaluate new therapies for severe sepsis in control mortality (8%), and the inclusion of all comers (with and current times, the following effective sample sizes of negative without severe sepsis) to a surgical ICU in the intensive insulin trial evidence were analyzed for each new therapy: Enthusiastic (n = 1); [6], we will evaluate the prospectively defined ‘‘.5 days in ICU’’ Mildly skeptic (n = 200); Mild-moderately skeptic (n = 500); sub-population. This subgroup control had mortality rates (20%) Moderately skeptic (n = 1,000); Severely skeptic (n = 2,000). We closer to those of the other trials. The rhAPC trial [3] will have two consider the current probability of ln(OR) .20.05 being less than analyses, since the drug was FDA approved based on the sicker 0.05 as sufficient evidence to conclude that the new treatment is (APACHE II .25) sub-population. Even though the ARDSNet better than the control. For example, if the clinician sums up Low-Tidal Volume trial [5] was not specifically designed for approximately 500 subjects from 3 previous negative trials on low- patients with severe sepsis, we included it because approximately tidal volume therapy [69–71] (i.e. mild to moderate skeptic about 60% of the trial population had sepsis or pneumonia, and the trial this therapy), our analysis (table 1) will provide a 0.05 current results have been recommended for patients with severe sepsis by probability of low-tidal volume therapy being no better than control. As the reader can appreciate in table 1, because of thenegative prior information that needs to be overcome, this current probability (0.05) is different from the classic p value reported inthe original trial publication (p = 0.007).
1. What is the current probability that the new therapy is 2. What is the current probability of decreasing the not better than the standard of care in my patient with relative risk of death of my patient with severe sepsis by a Table 1 shows the current probability of the new treatment clinical trials already published [1], the recent FDA approval of a being no better than the control. If we are enthusiastic about the new therapy on sepsis [3], and a 28-day mortality ranging from five trials, all probabilities are small. If we are just mildly skeptic, 30–40%, no new therapy for severe sepsis will likely be acceptedby clinicians or regulators if the relative risk reduction (RRR) formortality is not greater than 15–25% (absolute risk reduction Table 2. Probability of Relative Risk Reduction (RRR) of (ARR) $5–10%). For example, a trial with a control arm mortality of 30% and a experimental arm mortality of 25% would result inan ARR = 5% and a RRR = 16%. Thus, we will present the current probabilities for greater than 15%, 20%, and 25% RRRfor mortality in each trial (see Appendix S1). This second analysis can be thought of as analogous to ‘clinical significance’. For example, if the clinician sums up approximately 1000 subjects from 2 previous negative trials on volume replacement/vasopressor use [45,46] (i.e. moderate skeptic about this therapy) and believes that a minimum of 15% RRR needs to be demonstrated to add the EGDT to standard of care of patients with severe sepsis, our analysis (table 2) will provide a 6% current probability of reaching at least this RRR in mortality. This current probability (6%) of reducing mortality by at least 15% is differentfrom the classic overall RRR reported in the original trial the probabilities from the EGDT [2] and Low-Dose Steroid [4] Table 3. Probability of Relative Risk Reduction (RRR) of trials become 0.05 or larger, which may not provide strong enough evidence to change the standard of care. If we take into accountthe preceding multitude of unfavorable trials and analyze theseresults in the light of a mild-moderate skeptical view, the current probabilities for these two trials rise to 0.14 and 0.21, respectively.
The results of rhAPC, Low-Tidal Volume, and Intensive Insulin trials remain acceptable if we assume a mild skepticism-all withcurrent probabilities of less than 0.05. The mild-moderate skeptic analysis makes both the Low-Tidal Volume and Intensive Insulin results reach the 0.05 probability of the new treatment being no better than the control, and the moderate skeptic analysis showsthe rhAPC trial with the same 0.05 probability as well. The rhAPC APACHE II sub-analysis shows probabilities below 0.05 in all prior levels except in the severe skeptic analysis. If the clinician is severely skeptical, no trial results will lead to changes in thestandard of care.
2. What is the current probability of decreasing the relative risk of death of my patient with severe sepsis by Table 2 illustrates the current probabilities of achieving at least a specific clinically meaningful RRR based on the chosen cut-off andprior distribution. For a clinician who is enthusiastic (i.e. choosing the enthusiastic prior) about EGDT and believes that an RRR should not be less than 20% to use this new therapy in patient care, the chance of EGDT to decrease the relative risk of death more than20% is 87%. If RRR.15% is the goal, this therapy will have a 94% (enthusiastic) and 62% (mildly skeptic) current probabilities. This is atangible and easy result to translate and apply to bedside. For the mildly skeptic requiring a RRR.20% the probability drops to clinician who is mildly skeptical about this therapy, the chance of 37%, and for the mild-moderate skeptic requiring any RRR, the EGDT to decrease the relative risk of death more than 20% in a probabilities of benefit from this therapy remain all below 40%.
given patient will decrease to 41%, which may be too low for general The Intensive Insulin trial (table 6) shows consistent probabil- clinical application. If a moderately skeptical prior is applied to this ities of reducing the risk of death (69–98%) for all RRR levels in trial, the probability of having a RRR greater than 15% and 20% both enthusiastic and mild skeptic analyses. The probability drops substantially to 6% and 1%, respectively.
remains above 60% even in the mild-moderate skeptic analysis if For the rhAPC overall results (table 3), in the best case scenario the aim is a RRR.15%. However, for the moderate or severe (enthusiastic), the current probability of reaching a 20% RRR in skeptic approach, all results are below 42%.
mortality is 43%. If the clinician is comfortable with a 15% RRR,then the probability of reaching this cut-off with rhAPC goes up to 75% for the enthusiastic, and to 65% for the mildly skeptical, butremains low at 30% for the moderately skeptical. On the other The first analysis indicates that there is sufficient evidence to side, if we analyze this trial based on APACHE II .25 subgroup support the efficacy in all five trials only if we are enthusiastic with and enthusiastic prior, then there is 97%, 90%, and 72% respect to the prior distribution of each of these therapies. If we probability of respectively reaching RRR of 15%, 20%, and analyze them with the mild skepticism, only the Intensive Insulin, 25% with rhAPC. These are more optimistic results than the rhAPC, and Low-Tidal Volume trials show beneficial results.
overall trial analysis, but if the clinician remains a mild-moderateskeptic, the probability of achieving any of those same RRR Table 4. Probability of Relative Risk Reduction (RRR) of thresholds becomes smaller; 63%, 30%, and 7%, respectively. The moderate and severe skeptic analyses show most probabilities ofreaching any meaningful RRR in the single digits.
The Low-Dose Steroid trial analysis demonstrates well the importance of this type of clinical threshold analysis. In the bestcase-scenario for the least meaningful RRR (15%), the enthusiastic approach shows a current probability of 58% (table 4). Even for the mildly skeptic, steroids have an unacceptably low current probability (20% or less) of reaching any meaningful RRR in mortality. We also performed an additional analysis about theprobability of steroids reaching a RRR.10%, but except for the enthusiastic prior (76%), all other probabilities remain similarly The Low-Tidal Volume trial (table 5) shows a current probability of 83% (enthusiastic) or 65% (mild skeptic) for thephysician who is looking for a RRR.15%. However, for the than 20%. On the other hand, if we are mildly skeptical and aim a Table 5. Probability of Relative Risk Reduction (RRR) of RRR.15%, the probability of reducing the risk of death is 88% for the Intensive Insulin trial, 62–65% for the rhAPC, Low-TidalVolume, and EGDT trials, and just 17% for the Low-Dose Steroidtrial. Unless we are less ambitious with respect to the RRR, i.e.
15%, and accept an enthusiastic to mildly skeptic prior, none of these trials have shown strong enough evidence for diminishing the risk of death in patients with severe sepsis. Of note, the consistently very low current probabilities (poor strength of evidence) ofobserving mortality reduction with Low-Dose Steroids in both of our analyses (questions 1 and 2) was just confirmed by a recently published phase III trial [66]. Interestingly, our statistical analysis predicting the poor results of Low-Dose Steroids was completed and submitted long before the report of this new phase III trial.
We would like to recognize some limitations of our study. The statistical approach we used for this study may appear to produce more conservative results than conventional methods, but this is,in fact, the main strength of our data. The Bayes’ theorem is Although the rhAPC APACHE II .25 sub-analysis remains uncontroversial if derived from known data [88]. We strongly beneficial in the moderate skeptic analysis, the original results have believe that the prior negative evidence is so abundant that we not been validated in a prospective phase III trial yet. Based on have the ethical obligation to consider and use this methodology in our current results indicating high probability of new treatment the analysis of any new therapy for severe sepsis. The different being no better than controls in all skeptic analyses for the EGDP sample sizes of each trial may have influenced the current and Low-Dose Steroid trials, as well as on the numerous probabilities of our first analysis, but the consistent results found in unfavorable trials evaluating different regimens of volume both first and second analyses make the sample size influence less replacement/vasopressors or steroids in severe sepsis, we demon- likely. Also, because some of the therapeutic interventions were strate that the beneficial results from these two trials are the ones not identical within a specific class, and other studies were different with the weakest strength of evidence. All five trials become with respect to their trial design, we advise the reader to carefully unacceptable if we are moderately or severely skeptical, because evaluate the most appropriate priors to avoid overt pessimistic or the current probability of the new therapy being no better than the control is too high for general clinical application. The fact that In conclusion, our study provides four clinical and research most overall beneficial results are not even that impressive with the lessons with profound implications to the care of our patients with mild-moderately skeptic analysis is concerning.
The second analysis based on a specific clinical cut-off of the RRR brings important light to the interpretation of these trials.
Assuming an enthusiastic prior, the Intensive Insulin, the rhAPC Our results unambiguously demonstrate that it is important to APACHE II .25, and the EGDP trials demonstrate the highest replicate the results of each of these trials in well designed probability (87–96%) of reaching an RRR of at least 20% for confirmatory studies if we want to provide patient care based on mortality. However, the absence of a majority of patients with scientifically sound evidence. Further, the many study design issues severe sepsis in the Intensive Insulin trial, the absence of raised, e.g. standard of care of control groups (EGDT and Low- prospective validation of the rhAPC APACHE II .25 subgroup Tidal Volume trials [10–12,17,21–24]; the rhAPC APACHE II population, and the weak strength of evidence from our first .25 subgroup analysis without prospective validation [3] and the analysis for the EGDP trial, all suggest that more skepticism should poor results of this subgroup in the ADDRESS trial [49,89]; the be taken before assuming these probabilities of RRR.20%. In controversial definitions of adrenal insufficiency [20,90,91], and this case, the moderate skeptic analysis for these 3 trials shows all the just reported Low-Dose Steroid phase III trial with negative current probabilities of 23% or less of reducing death risk by more results [66]; and the failure of the Intensive Insulin Therapy toimprove survival in the medical ICU population [75] allcorroborate our conclusion for lesson 1.
Table 6. Probability of Relative Risk Reduction (RRR) ofMortality by Intensive Insulin Therapy.
Lesson 2–Standard of care for patients with severe sepsis The strength of evidence (statistical and clinical) is overall weak for the five trials. These results make any legitimate changes in the standard of care a very difficult task to accomplish. While we endorse the genuine need for more evidence, we are aware of the urgent need to improve the survival outcome of our patients with severe sepsis. How to reconcile this apparent conundrum? SirAustin Hill already had the answer in his seminal paper from 1965: ‘‘All scientific work is incomplete–whether it be observa- tional or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer on us a freedom to ignore the knowledge that we already have, or topostpone the action that it appears to demand at a given time’’ [92]. Before we have the results of confirmatory trials, we urge clinicians to use our clinical threshold analysis of RRR for mortality from each trial (tables 2–6) to guide the best course of We anticipate that our comprehensive analysis and interpreta- action to take for their patients with severe sepsis.
tion of these trials will bestow realistic and practical tools toclinicians to decide on their own and without undue influence how Lesson 3–No need for changes in the measurement of to best apply the results of these trials to their patients with severe The most important premise to change the measurement of quality of care must be based on strong and established scientific evidence, but this is lacking at this time. When we completed our study it became obvious that, with such low strength of evidence Found at: doi:10.1371/journal.pone.0002291.s001 (0.05 MB and critical need for confirmatory trials, none of these studies’results should be applied as rigid tools to measure quality of care in patients with severe sepsis in the ICU.
Lesson 4–Need for both classic and Bayesian The authors thank Ms Elaine Litton for providing outstanding adminis- As we demonstrate in this paper, the dual use of these methods is powerful and synergistic to accomplish an ample interpretation of these pivotal trials. We strongly suggest that trialists, sponsors, Conceived and designed the experiments: AK JS. Performed the regulators, and journal editors become more proactive with experiments: AK JS. Analyzed the data: AK JS. Wrote the paper: AK respect to the use of this dual statistical approach. Patients will be the ultimate beneficiaries from this more encompassing strategy.
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Source: http://www.bayes.it/pdf/Kalil_Sun.pdf


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Assignment 1: module 1-3

MPH5041, 2013 Biostatistics for Clinical and Public Health Research Test 3, Due April 26, 2013 by 11:59pm Modules Covered: This Test covers Modules 1-5. All questions must be answered using statistical knowledge in Modules 1-5 only. SPSS or any other statistical package can be used for data analysis . Assignment General Instructions: This test is wort

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