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Risk and the Efficacy of Antiinflammatory Agents

Retrospective and Confirmatory Studies of Sepsis

Critical Care Medicine Department, National Institutes of Health, Bethesda, Maryland

Correspondence and requests for reprints should be addressed to Peter Q. Eichacker, M.D., Critical Care Medicine Department, National Institutes of Health, Building 10, Room 7D43, 10 Center Drive, MSC 1662, Bethesda, MD 20892–1662. E-mail: peichacker{at}nih.gov

	ABSTRACT

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We investigated whether a relationship between risk of death and treatment effect could explain the disparate results between the preclinical and clinical sepsis trials of antiinflammatory agents over the last decade. A metaregression analysis of cited preclinical studies showed that the treatment effects of these agents were highly dependent on risk of death (p = 0.0001) and that animals were studied at significantly higher control mortality rates than humans (median [25th–75th quartile], 88% [79–96%] versus 39% [32–42%], p = 0.0001). An analysis of the clinical trials showed that antiinflammatory agents were also significantly more efficacious in septic patients with higher risk of death (p = 0.002) and were harmful in those with low risk. To test this relationship prospectively, we studied antiinflammatory agents in models employing differing doses of bacterial challenge to produce the full range of risk of death. We found that the efficacy of these agents, although very beneficial at high control mortality rates, was much reduced (p = 0.0001) and similar to those in human trials at moderate control mortality rates (i.e., 30 to 40%). The efficacy of antiinflammatory agents during sepsis is dependent on the risk of death, an observation that explains the apparent contradiction between preclinical and clinical trial results. Accounting for this relationship may be necessary for the safe and effective development of antiinflammatory therapies for sepsis.

Key Words: septic shock • preclinical and clinical trials • metaregression analysis • antiinflammatory therapies

	INTRODUCTION

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Despite promising preclinical testing (1–38) and the expenditure of several billion dollars, antiinflammatory agents designed to inhibit specific host mediators during sepsis failed to show benefit in 22 clinical trials involving over 10,000 patients (Table 1) (39–60). This failure for the global pharmaceutical industry and academic community has been much discussed but never adequately explained. The underlying hypothesis of this therapeutic approach—that the intense host inflammatory response becomes pathogenic in severe sepsis and septic shock—has been questioned but not refuted (61–65). Even if this hypothesis is incorrect or its successful application requires the blockade of different or multiple targets in the host response to infection, it would not explain the marked disparity in the efficacy of these mediator-specific antiinflammatory agents comparing animal models of sepsis to infected patients. Identifying factors underlying this difference between clinical and preclinical trials would likely strengthen the development and application not only of antiinflammatory agents but also of other new therapies for sepsis.

To test the potential relationship between risk of death and the efficacy of antiinflammatory agents in sepsis, we first examined the published preclinical trials used to support testing mediator-specific antiinflammatory agents in septic patients. None of these individual animal studies examined this relationship. We then analyzed the treatment effect across published studies in a metaregression analysis to see whether it changed as risk of death varied. This led us to perform a similar analysis of the clinical trials themselves, looking separately at those trials that stratified patients' treatment effect based on their predicted risk of death and then those that did not. Finally, we prospectively tested in our own laboratories the influence of risk of death on antiinflammatory agents by altering the dose of bacterial-challenge animals received and thereby mortality rates. This allowed us to examine animal studies at lower risks of death more similar to human sepsis studies. In addition, the route and type of challenge and type of antiinflammatory agent studied were varied because these factors had also been proposed as a basis for the differing effects of antiinflammatory agents (61–65). As a control, we tested the influence of risk of death on fluid therapy, a conventional treatment for sepsis not known to have antiinflammatory effects.

Our metaregression analyses of published preclinical and clinical sepsis trials and confirmatory prospective animal sepsis studies each showed similarly that the risk of death influences the effects of antiinflammatory agents in sepsis. This relationship explains the contradictory results noted in prior preclinical and clinical trials. More importantly, accounting for this relationship may be necessary for the safe and effective development of new agents for the treatment of sepsis and septic shock.

	METHODS

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Analysis of Published Preclinical Studies
Twenty-two clinical trials (39–60) were conducted between January 1986 and January 2000 that tested the effects of seven different nonsteroidal mediator-specific antiinflammatory agents (i.e., anti-TNF [tumor necrosis factor] antibodies, P-55 and P-80 TNF-soluble receptors [sometimes referred to as the P-75 TNF-soluble receptor], interleukin-1 receptor antagonist, platelet-activating factor receptor antagonist, antibradykinin, and antiprostaglandin) (see online data supplement) (72). To investigate the basis for the differing effects that these agents were reported to have in animal models versus human trials, all preclinical studies cited to support their use in clinical trials were reviewed for this metaregression analysis (1–38). All reported experiments in these studies were included provided that survival rates of the treatment agent were directly compared with a survival rate of a placebo or lower dose treatment group. In addition, in all experiments, the type and route of septic challenge, the regimen of treatment employed, including both timing and dose, the species studied, and the duration of observation were recorded for analysis.

For each experiment, treatment mortality rate was plotted on the y axis and the corresponding control mortality rate on the x axis, yielding a graph on the unit square in which each axis represents fully independent measures. To avoid constraining data at the extremes of the mortality rate ranges, we reparameterized the unit square to occupy the whole plane (73). The y axis was transformed to become the log of the odds of treatment mortality and the x axis to become the log of the odds of control mortality. A weighted linear regression based on the number of animals in each study was performed. Although the analysis was always done with the y axis expressed as the log of the odds of treatment mortality, for ease of presentation, the results are presented with the y axis expressed as the log odds ratio of survival. The odds ratio of survival is the odds of survival in the treatment group divided by the odds of survival in the control group. The odds ratio of survival is mathematically equivalent and is a commonly used measure of efficacy in clinical trial literature. No other factor examined (i.e., type or route of septic challenge, regimen of treatment, including timing and dose, duration of observation, or species studied) significantly changed (all p > 0.20) the relationship between treatment effect and control mortality rate (74).

Analysis of Published Clinical Trials
We assessed the consistency of the clinical trials by determining whether the odds ratios of the 22 human sepsis trials fell within the 95% confidence interval for the mean regression line calculated with the preclinical animal studies. In addition, two trials stratified patients based on the predicted risk of death, and these trials, along with the remaining 20 studies, were analyzed in a manner similar to the published preclinical studies.

Prospective Preclinical Studies
To examine prospectively the relationship between risk of death and treatment effect with antiinflammatory agents in sepsis, Sprague-Dawley rats (n = 1,296) were randomized to be challenged intravenously or intrabronchially with varying doses of Escherichia coli 0111:B4, Staphylococcus aureus (0.25 to 100 x 10⁹ CFU · kg^-1 body weight), or E. coli 0111:B4 endotoxin (0.75 to 2 µg · kg^-1; Sigma, St. Louis, MO). These differing bacterial doses, types, and routes of challenge were studied to attempt to simulate the diverse types of infection that would be present in a population of septic patients producing a wide range of mortality rates. We studied antiinflammatory agents with different mechanisms of action to examine prospectively whether the effect of risk of death is dependent on one type of immunomodulator. After challenge, one group of animals (n = 653) was treated with high molecular weight TNF-soluble receptor (P-80 TNF-soluble receptor; 100 µg · kg^-1 intravenously; Immunex, Seattle, WA) or placebo. This agent was significantly harmful in a clinical sepsis trial (48) after animal studies had shown it to be beneficial in a highly lethal gram-negative bacterial or bacterial toxin model (23). Another group of animals (n = 638) received a tyrosine kinase inhibitor (75–81) (tyrphostin AG556, 2.5 µg · kg^-1, intraperitoneally) or placebo given immediately and 6 hours after challenge to examine an antiinflammatory agent that blocks the release of multiple inflammatory mediators simultaneously (75–81) rather than directly neutralizing circulating TNF. To investigate whether risk of death affected the efficacy of a conventional sepsis treatment, an additional group of rats (n = 192) was challenged with varying doses of E. coli and then treated with or without normal saline (20 ml · kg^-1h^-1 intravenously for 24 hours) (82). All animals received daily antibiotics for 3 days, and after 7 days, animals were considered survivors as previously described (83).

The relationship between risk of death and treatment efficacy was examined in a manner similar to the published animal studies, and these relationships were not significantly changed (p > 0.20) by any of the other variables studied. The consistency of this data with published preclinical and clinical trials was assessed as previously described.

All animal protocols used in these studies were approved by the Animal Care and Use Committee of the Clinical Center of the National Institutes of Health. Every effort was made to minimize animal suffering during these protocols. The research protocols required the veterinarian staff or principle investigators to euthanize any animal that experienced unexpected severe pain or distress.

	RESULTS

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Published Preclinical Studies of Antiinflammatory Agents
In 22 human sepsis trials of antiinflammatory agents (Table 1) (39–60), a total of 38 animal sepsis studies were cited (95 individual experiments; Figures 1A–1C) (1–38). Animals were studied at much higher control mortality rates than humans (median [25th–75th quartile] 88% [79–96%] versus 39% [32–43%], p = 0.0001) (Figures 1B and 1C). Regardless of the type of challenge, timing or dose of treatment, species studied, or duration of observation, the odds ratio of survival with all mediator-specific antiinflammatory agents diminished as the risk of death (control mortality rate studied) decreased (p = 0.0001) (Figure 1). Notably, anti-TNF antibodies were found to be significantly harmful in two animal studies cited with very low (less than 15%) control mortality rates that were below those studied in most clinical and preclinical sepsis trials (17, 18). Each of these two studies significantly increased the slope of the relationship between risk of death and treatment. Although shown with other data, because these two studies were overly influential, they were excluded from analysis; however, inclusion would make this relationship even stronger. Among all factors examined, risk of death explained the majority of the variability (70%) in the treatment effects of antiinflammatory agents comparing these 95 experiments.

View larger version (26K): [in this window] [in a new window]   Figure 1. (A–C) The weighted regression line in A shows the relationship between control odds and the odds ratio of survival with treatment for 95 experiments (open circles) in 38 published animal studies cited (1–38) in 22 clinical sepsis trials of mediator-specific antiinflammatory agents (Table 1) (39–60). B is the same as A but also shows the control odds and odds ratio for survival for the 22 clinical trials (open diamonds) (39–60) testing mediator-specific antiinflammatory agents. C divides the data in B by type of antiinflammatory agent. The circle size in each panel is adjusted for the number of animals in each experiment, but not the diamond size in B and C because the number of patients in each trial was not used to calculate the weighted regression line.

View larger version (21K): [in this window] [in a new window]   Figure 2. A compares the treatment effect of mediator-specific antiinflammatory agents in 22 clinical trials (39–60) (open diamonds) (Table 1) to the 95% confidence interval (gray bar) for the regression line describing their effects in cited animal studies (1–38) from Figure 1A. B and C compare these same 22 clinical trials to the 95% confidence interval (gray bars) for the regression line describing their effects in prospective animal studies testing either antiinflammatory agents from Figure 4A or fluid support in animals from Figure 4B, respectively. Because preclinical trials included fewer subjects than clinical ones, for ease of presentation, these confidence intervals are adjusted for the median number of patients in clinical trials. However, all comparisons in the results section were based on actual numbers of animals or patients in each trial.

View larger version (27K): [in this window] [in a new window]   Figure 4. (A–C) This format is similar to Figure 1 except that here each circle represents an experiment in which we prospectively challenged animals with a dose of bacterial challenge designed to produce a range of mortality rates and then treated them with an antiinflammatory agent or placebo (A). In B, the format is similar to A except now each circle represents an experiment in which we prospectively challenged animals with a differing dose of bacteria and then either did or did not treat with fluids. C divides the data in A by type of antiinflammatory agent used as well as by the type and route of bacterial challenge.

View larger version (20K): [in this window] [in a new window]   Figure 3. (A–C) In one phase III trial of interleukin-1 receptor antagonist and one of P-55 TNF-soluble receptors, septic patients were categorized at study entry into groups based on their predicted risks of death, as determined by a modified Acute Physiology and Chronic Health Evaluation II or Stratified Acute Physiology score, respectively (open diamonds) (50, 53, 66). Using the same format as Figure 1, A shows the observed control odds and odds ratio of survival with antiinflammatory treatment for these risk categories as well as the weighted regression line for the relationship. B shows the relationship between the overall control odds and odds ratio of survival for the remaining 20 trials of antiinflammatory agents (39–49, 51, 52, 54–60) that did not provide segregated data like that shown in A. C divides the data from A by type of antiinflammatory agent. The size of the diamonds in each panel is adjusted to the number of patients in each subgroup (A and C) or trial (B) because a weighted regression analysis was done.

For our prospective and previously unpublished studies (Figure 4A) and the published preclinical studies from other laboratories (Figure 1A) of antiinflammatory therapies, the slopes of this regression relationship comparing risk of death and treatment effect were similar (0.40 versus 0.48, respectively, p = NS). However, the y intercept was greater in the published compared with the prospective preclinical studies (2.95 versus 1.17, respectively, p = 0.0001) (Figures 1A and 4A). The greater beneficial effects and increases in y intercept in published versus prospective studies can be partially explained as positive results are more likely to be published, causing an overestimation of treatment effects (84). All 22 clinical trials fit within the 95% confidence interval for the odds of survival in these prospective preclinical trials of antiinflammatory agents (Figure 2B).

In this preclinical model, fluid therapy had a significantly different relationship (i.e., slope and intercept) between risk of death and treatment effect (Figure 4B) compared with antiinflammatory agents in prospective studies (p = 0.008 for both slope and intercept) (Figure 4A). After E. coli challenges, fluids produced significant beneficial effects that were similar regardless of control mortality rate. At comparable control mortality rates, only 4 (39, 45, 51, 57) of the 22 (39–60) clinical trials fit within the 95% confidence interval for the effects of fluid therapy in animals (Figure 2C). Notably, more of the 22 clinical trials fit within the 95% confidence intervals for survival with antiinflammatory therapies than with fluid therapy in animals (22 of 22 versus 4 of 22, respectively; p = 0.0001) (Figures 2B and 2C).

Comparison of Time of Observation Used to Calculate Survival Rates in Animals and Human Sepsis Studies
In this meta-analysis, we analyzed survival rates and not survival times because this was the only outcome measure universally reported. Differences in follow-up times within species or differing life spans across species could potentially produce differences in control mortality rates and thereby alter the relationship between control mortality rate and treatment effect. The median (range) duration of follow-up for determining survival rates in published animal studies was 168 hours (24 to 288 hours) in rats, 75 hours (24 to 360 hours) in mice, 72 hours (24 to 336 hours) in primates, and 24 hours (5 to 168 hours) in rabbits. For these previously published animal studies, there was no significant correlation between control mortality rate and the length of follow-up time within or across these species (r values, 0.30 to -0.14; p values, 0.40 to 0.98). Therefore, in the published animal studies, differences in follow-up times cannot explain the significant relationship found between increasing control mortality rate and the treatment effects of antiinflammatory agents. All of our prospective animal studies were based on 7-day survival rates, and all of the human clinical sepsis trials were based on 28- to 30-day survival rates. Therefore, differences in follow-up times also cannot explain the significant relationship found between control mortality rate and treatment effects of antiinflammatory agents in either our animal studies or the human sepsis trials. Finally, because the time of observation after treatment was actually much longer in human sepsis trials than all of the preclinical sepsis studies examined, it is unlikely that this variable caused the significantly higher control mortality rates found in animal compared with human sepsis studies.

	DISCUSSION

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In a retrospective analysis of clinical and preclinical trials and confirmatory animal studies, we found that risk of death altered the efficacy of antiinflammatory agents during sepsis. This relationship provides an explanation for the contradictory results noted with this therapeutic approach in preclinical (1–38) and clinical sepsis trials (39–60) over the past decade. Antiinflammatory agents had greater treatment effects in animal models compared with clinical trials because preclinical studies were done at significantly higher risks of death (Figure 1). Furthermore, human trials of antiinflammatory therapies failed because they enrolled patients at a level of risk where these agents have minimal effects (Figure 1 and Table 1). Animal studies we conducted at low risks of death produced the same results seen in septic patients (Figure 2B). A small number of published animal studies conducted at low control mortality rates (Figure 1) (17, 18) demonstrated that antiinflammatory agents in sepsis have the potential to be harmful in less severely ill subjects. This effect is consistent with the adverse outcome seen after P-80 TNF-soluble receptor administration in a subgroup of patients with gram-positive infection that had a low control mortality rate (13%) (48) (Figure 4C).

Two clinical trials provided data that categorized patients into groups based on their predicted risk of death (50, 53, 66). These trials allowed us to evaluate the effects of two different agents over a range of control mortality rates similar to the animal studies. Just as in animal studies, these agents were most beneficial in those groups of patients with high risks of death and were harmful in those with low risks (Figure 3A). The other 20 sepsis trials (39–49, 51, 52, 54–60), studied over a more limited range of control mortality rates, showed a very similar relationship between risk of death and treatment effects (Figure 3B). We believe that this consistency among preclinical studies from different laboratories and clinical trials strongly supports our hypothesis that risk of death alters the effects of antiinflammatory agents during sepsis.

Results of a phase III sepsis trial of activated protein C (APC), an agent with antiinflammatory and antithrombotic properties, could be an exception to our findings because of a highly significant (p = 0.005) beneficial effect. Therefore, this agent deserves comparison to these clinical trials even though published after completion of this metaregression analysis (Figure 5A) (85, 86). Although APC significantly improved survival rates compared with standard sepsis therapies, its treatment effect was not significantly different compared with the combined effects of all these previously studied mediator-specific antiinflammatory agents (n = 22) (p = 0.10) (Figure 5A) or the phase III trials of these agents (n = 9) (odds ratio [95% confidence interval]; 1.36 [1.10, 1.68] versus 1.13 [1.03, 1.24], respectively, p = 0.20) (Table 1) (39–60). Furthermore, a prospective analysis divided the 1,690 patients in the clinical APC trial into four equal groups based on Acute Physiology and Chronic Health Evaluation II scores (85–87). Similar to clinical trials of the other antiinflammatory agents, APC was less beneficial (odds ratio of survival 1.56, 1.82, 1.19, and 0.77, respectively) as control mortality rates (49, 36, 26, and 12%, respectively) and Acute Physiology and Chronic Health Evaluation scores decreased (52–30, 29–25, 24–20, 19–3, respectively) (Figure 5B). Accordingly, APC was licensed for use by the Food and Drug Administration for only patients with severe sepsis (sepsis associated with acute organ dysfunction) and a high risk of death (e.g., as determined by Acute Physiology and Chronic Health Evaluation II scores) (87). Because of the consistency of the APC data to our findings (Figure 5) examining other antiinflammatory agents, it must be considered that in patients with a low risk of death, APC may not only be ineffective but also harmful.

View larger version (15K): [in this window] [in a new window]   Figure 5. (A and B) This figure shows the results of the clinical (85) and cited preclinical (86) sepsis trial of APC (open diamond and circle in A) as well as the effects of APC in patients categorized based on their predicted risk of death (87) (open diamonds in B). For comparison, in A, data are included from Figure 1 (gray diamonds and circles) and in B from Figure 3 (gray diamonds).

Our model also has a term predicting the treatment efficacy of an agent at a 50% control mortality rate. If this value had actually been very high for the agents we analyzed, then the slopes for the regression lines reported might have been of little consequence. In this case, although the efficacy of antiinflammatory agents might decrease as risk of death decreased, it would still be beneficial throughout the entire range of control mortality rates. However, in most of our analyses, these terms were relatively small. With such small treatment effects at a 50% control mortality rate (odds ratio, 1.17 to 1.48), any significant change in efficacy as control mortality rate decreases becomes worrisome because at low risks of death (i.e., less than a 50% control mortality rate) these agents become harmful. It would be ideal to find an antiinflammatory agent for sepsis that functions as fluids did, with a relatively large treatment effect at a 50% control mortality and a relatively small slope. Such an agent would be beneficial over the full range of control mortality rates.

For a highly lethal disease such as sepsis, use of preclinical studies conducted over a wide range of risk may provide a transformative method for the preclinical testing of new agents. They permit an estimation of an agent's treatment effect at a 50% mortality rate and can demonstrate the influence risk of death may have on the agent's efficacy. Together, these data suggest whether there is a level of risk below which an agent may produce harm. Ideally, drugs taken into clinical testing would be those that have significant beneficial effects over a wide range of competing risks. However, a different approach must be considered if preclinical or later clinical testing indicates that an agent is beneficial above, but harmful below, a particular risk of death. Subsequent clinical trials should then incorporate entry and exclusion criteria such as risk prediction scores to ensure that patients likely to benefit are included and that those likely to be harmed are excluded. Examining this relationship between risk of death and treatment effect preclinically and then using this information to optimally design the clinical trial are likely to reduce the size and expense of human research in highly lethal disease and may also help minimize the risk of drug-related fatalities.

	FOOTNOTES

 
This article has an online data supplement, which is accessible from this issue's table of contents online at www.atsjournals.org

Received in original form April 9, 2002; accepted in final form July 16, 2002

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