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Overall Survival Endpoint in Oncology Clinical Trials: Addressing the Effect of Crossover - The Case of Pazopanib in Advanced Renal Cell Carcinoma
Abstract
Objective:
To identify the issues of using overall survival (OS) as a primary endpoint in the presence of crossover and the statistical analyses available to adjust for confounded OS due to crossover in oncology clinical trials.
Methods:
An indirect comparison was conducted between pazopanib and sunitinib in advanced renal cell carcinoma. Statistical adjustment methods were used to estimate the true comparative effectiveness of these treatments. Recently, a head-to-head trial comparing pazopanib and sunitinib was completed. This provided the opportunity to compare the OS treatment effect estimated for pazopanib versus sunitinib using indirect comparison and statistical adjustment techniques with that observed in the head-to-head trial.
Results:
Using a rank-preserving structural failure time model to adjust for crossover in the pazopanib registration trial, the indirect comparison of pazopanib versus sunitinib resulted in an OS hazard ratio (HR) of 0.97, while an unadjusted analysis resulted in an OS HR of 1.96. The head-to-head trial reported a final OS HR of 0.92 for pazopanib versus sunitinib.
Conclusion:
This case study supports the need to adjust for confounded OS due to crossover, which enables trials to meet ethical standards and provides decision makers with a more accurate estimate of treatment benefit.
... The clinical outcomes of HSCT and their inter-relationship are complex and heterogeneous. Therefore, an in-depth endpoint analysis is imperative to advance the field [9]. Endpoint analyses have been performed for other hematologic malignancies, not HSCT [10]. ...
... However, extended trials must comprise enough events to reach a statistically significant conclusion for a 3-year prognosis [4]. OS can be confounded by multiple salvage attempts or death from other reasons, which brings its applicability as a predominant endpoint into question [4,9,11]. ...
... These methods apply counterfactual arguments to reconstruct data in the absence of switching, with the aim of reducing bias and allowing the treatment effect to be estimated more accurately. Such methods are widely accepted by regulators and health technology assessment bodies [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and are increasingly applied in cancer and a number of other therapeutic areas that apply time-to-event endpoints [14,16,18]. As yet, their application in PAH, where the use of long-term morbidity/mortality outcomes has replaced short-term outcomes only relatively recently, has not been published. ...
... These methods apply counterfactual arguments to reconstruct data in the absence of switching, with the aim of reducing bias and allowing the treatment effect to be estimated more accurately. Such methods are widely accepted by regulators and health technology assessment bodies [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and are increasingly applied in cancer and a number of other therapeutic areas that apply time-to-event endpoints [14,16,18]. As yet, their application in PAH, where the use of long-term morbidity/mortality outcomes has replaced short-term outcomes only relatively recently, has not been published. ...
Introduction:
Evaluating overall survival in randomized controlled trials (RCTs) can often be confounded by bias introduced by treatment switching. SERAPHIN was a large RCT that evaluated the effects of long-term treatment with the endothelin receptor antagonist macitentan in patients with pulmonary arterial hypertension. In an intent-to-treat (ITT) analysis, a non-significant decrease in the risk of all-cause mortality up to study closure was reported with macitentan 10 mg versus placebo. As patients could switch treatment when experiencing symptoms of disease progression, this analysis attempts to adjust for the confounding effects on overall survival.
Methods:
The inverse probability of censoring weighted (IPCW) and rank-preserving structural failure time (RPSFT) models were used to estimate the treatment effect on overall mortality had there been no treatment switching in SERAPHIN. Time to all-cause death was evaluated up to study closure. Treatment switching was defined as patients in the placebo group switching to open-label macitentan 10 mg, and patients in the macitentan 10 mg group prematurely discontinuing macitentan.
Results:
By study closure, 73.2% (183/250) of patients in the placebo group had switched to macitentan 10 mg. Among these patients, exposure time to macitentan 10 mg represented 28.2% of total study treatment exposure (cumulative exposure 134.6 patient-years). At study closure, 24.8% (60/242) of patients in the macitentan 10 mg group were not receiving open-label macitentan; mean time not receiving macitentan was 44.3 weeks. The adjusted hazard ratios (HR) for overall survival using the IPCW and RPSFT methods were lower (HR 0.42, 95% confidence interval [CI] 0.22, 0.81; p = 0.009, and HR 0.33, 95% CI 0.04, 2.83, respectively) than the ITT unadjusted HR (0.80, 95% CI 0.51, 1.24).
Conclusion:
These results from the current analyses indicate that in SERAPHIN, the standard ITT analysis was confounded by treatment switching resulting in an underestimation of the benefit of macitentan 10 mg on overall survival. By adjusting for switching, the IPCW and RPSFT models estimated a 58% and 67% reduction in risk of mortality, respectively, with macitentan 10 mg versus placebo.
Trial registration:
ClinicalTrials.gov identifier: NCT00660179.
... [27][28][29] RPSFTM is a well-recognized method for health technology assessment 28 and has been used to adjust for confounding effects of subsequent treatment in clinical trials of renal cell carcinoma; gastrointestinal stromal tumors; melanoma; ovarian cancer; neuroendocrine tumors; and, most recently, NSCLC. [30][31][32][33][34][35][36][37][38][39][40] Other methods include a 2-stage approach, which is appropriate when treatment switching is permitted after a disease-related time point such as disease progression. 27 The 2-stage method has found favor for health technology assessment when the required assumption of a common treatment effect for RPSFTM is not met. ...
Background
Historically, the standard of care (SoC) for patients with unresectable, Stage III non-small-cell lung cancer (NSCLC) had been concurrent chemoradiotherapy (cCRT). However, outcomes had been poor, with ∼15–32% of patients alive at 5 years. In the placebo-controlled Phase 3 PACIFIC trial, consolidation treatment with durvalumab after cCRT significantly improved overall survival (OS) and progression-free survival in patients with unresectable, Stage III NSCLC, establishing this regimen as a new SoC in this setting. In PACIFIC, crossover between treatment arms (durvalumab or placebo) was not permitted. However, after discontinuation from study treatment, patients from both arms could switch to subsequent anti-cancer therapy, including durvalumab and other immunotherapies, which is known to impact standard intention-to-treat (ITT) analysis of OS, potentially underestimating the effect of an experimental drug. Moreover, the introduction of immunotherapies has demonstrated marked improvements in the post-progression, metastatic NSCLC setting.
Objective
To examine the impact of subsequent immunotherapy on OS in PACIFIC.
Methods
Both a rank preserving structural failure time model (RPSFTM) and modified two-stage method (M2SM) were used. RPSFTM assumes that a patient's survival time with no immunotherapy (counterfactual survival time) is equal to the observed time influenced by immunotherapy, multiplied by an acceleration factor, plus the time not influenced. The modified two-stage method (M2SM) estimates the effect of immunotherapy by comparing post-subsequent-treatment-initiation survival times between patients with and without subsequent immunotherapy. In both models, OS was adjusted to reflect a hypothetical scenario in which no patients received subsequent immunotherapy. RPSFTM was also used for scenarios in which subsequent immunotherapy was received by increasing proportions of placebo patients but none of the durvalumab patients.
Results
In the ITT analysis (3-year follow-up), durvalumab improved OS versus placebo (stratified HR, 0.69; 95% CI, 0.55–0.86). Overall, 10% and 27% of durvalumab and placebo patients, respectively, received subsequent immunotherapy. With subsequent immunotherapy removed from both arms, estimated HR was 0.66 (95% CI, 0.53–0.84) with RPSFTM and 0.68 (95% CI, 0.54–0.85) with M2SM. With subsequent immunotherapy removed from the durvalumab arm only (RPSFTM), estimated HR increased as the proportion of placebo patients receiving subsequent immunotherapy increased, up to 0.75 (95% CI, 0.60–0.94) maximum (assuming all placebo patients with subsequent treatment received immunotherapy).
Conclusions
Results were consistent with the ITT analysis, supporting the conclusion that durvalumab after chemoradiotherapy provides substantial OS benefit in patients with Stage III, unresectable NSCLC.
Clinical Trials Registry
NCT02125461
... At the same time, crossover in combination therapy trials may have limited our ability to detect a survival advantage for patients receiving novel combination therapies. [35][36][37] Last, we used a simple measure of clinical impact-one that is insensitive to the magnitude of patient benefit, or quality of evidence, associated with regimens recommended by the National Comprehensive Cancer Network or approved by the Food and Drug Administration. For instance, approval or recommendation does not necessarily imply clinical benefit. ...
Background
After approval, drug developers often pursue trials aimed at extending the uses of a new drug by combining it with other drugs. Little is known about the risk and benefits associated with such research.
Methods
To establish a historic benchmark of risk and benefit, we searched Medline and Embase for clinical trials testing anti-cancer drugs in combination within 5 years of approval by the Food and Drug Administration of 12 anti-cancer “index” drugs first licensed 2005–2007 inclusive. Risk was assessed based on grade 3 or above drug-related adverse events; benefit was assessed based on efficacy outcomes and advancement of combinations into clinical practice guidelines or approval by the Food and Drug Administration.
Results
We captured 323 published post-approval trials exploring combinations, including 266 unique combination–indication pairings and enrolling 29,835 patients. The pooled risk ratios for treatment-related grade 3–4 severe adverse events and deaths attributed to the study drugs for trials randomized between a combination arm and a comparator were 1.54 (1.33–1.79) and 1.51 (1.16–1.97), respectively. The pooled hazard ratios for overall survival and progression-free survival were 0.99 (0.92–1.05) and 0.85 (0.79–0.93), respectively. None of the combination–indication pairings launched after initial drug approval received approval by the Food and Drug Administration, and 13 pairings (4.9%) were recommended by the National Comprehensive Cancer Network within 5 years of the first trial within that pairing. The proportion of patients in our sample who participated in trials leading to an approval by the Food and Drug Administration or a National Comprehensive Cancer Network guideline recommendation was 12.7% with 5 years of follow-up, and 22.3% among pairings for which there were 8 years of follow-up.
Conclusion
Patients were just as likely to benefit in the treatment arm as the control arm in terms of overall survival, but they were more likely to experience a treatment-related severe adverse event in post-approval trials of combination therapy.
... that the association between OS and PFS will never be definite, even within a given indication [28]. However, it may be challenging to establish a valid association in the first place if OS data from available trials are affected by crossover or any subsequent therapy after patients stop study treatment [29], which can be expected to be particularly relevant to studies in the front-line setting [30]. 2. Crossover after demonstration of superior efficacy in terms of OS The second scenario of a crossover trial design in oncology is the implementation of crossover following the demonstration that the investigational agent improves outcomes. ...
Background
In oncology clinical trials, crossover is used frequently but may lead to uncertainties regarding treatment effects.
Objective
To investigate the handling of evidence from crossover trials by the European Medicines Agency (EMA) and the German Federal Joint Committee (G-BA).
Methods
For oncology medicines with early benefit assessments before January 2015, presence of crossover, clinical data, EMA requests for additional data, and G-BA benefit ratings/evidence levels were analyzed from manufacturers’ dossiers, G-BA appraisals, European Public Assessment Reports, and original publications.
Results
Eleven of 21 benefit assessments included crossover trials. Significant intergroup differences (P < 0.05) in overall survival (OS) were noted in 7 of 11 trials with and 7 of 10 without crossover. For 6 of 11 medicines with crossover, these were demonstrated before crossover. Treatment effects generally worsened with increasing proportions of crossover. The EMA requested additional data more frequently if crossover was performed, particularly if no OS data were available before crossover. The G-BA granted a considerable benefit to 73% of medicines with crossover and 40% of those without. Evidence levels were intermediate for 50% and 75%, respectively. None of the medicines received the highest evidence level.
Conclusions
In G-BA appraisals, oncology medicines with crossover received better additional benefit ratings, but were assigned lower evidence levels, than those without. The five medicines with crossover after progression were assigned lower evidence levels than the six medicines with crossover after demonstration of superior OS, indicating that the way in which crossover is implemented may be one factor influencing the assignment of evidence levels by the G-BA.
Oncology has been one of the most active therapeutic areas in medicinal products development. Despite this fact, few drugs have been approved for use in pediatric cancer patients when compared to the number approved for adults with cancer. This disparity could be attributed to the fact that many oncology drugs have had orphan drug designation and were exempt from Pediatric Research Equity Act (PREA) requirements. On August 18, 2017, the RACE for Children Act, i.e. Research to Accelerate Cures and Equity Act, was signed into law as Title V of the 2017 FDA Reauthorization Act (FDARA) to amend the PREA. Pediatric investigation is now required if the drug or biological product is intended for the treatment of an adult cancer and directed at a molecular target that FDA determines to be "substantially relevant to the growth or progression of a pediatric cancer." This paper discusses the specific considerations in clinical trial designs and statistical methodologies to be implemented in oncology pediatric clinical programs.
Background:
The rank-preserving structural failure time model (RPSFTM) is used for health technology assessment submissions to adjust for switching patients from reference to investigational treatment in cancer trials. It uses counterfactual survival (survival when only reference treatment would have been used) and assumes that, at randomization, the counterfactual survival distribution for the investigational and reference arms is identical. Previous validation reports have assumed that patients in the investigational treatment arm stay on therapy throughout the study period.
Objectives:
To evaluate the validity of the RPSFTM at various levels of crossover in situations in which patients are taken off the investigational drug in the investigational arm.
Methods:
The RPSFTM was applied to simulated datasets differing in percentage of patients switching, time of switching, underlying acceleration factor, and number of patients, using exponential distributions for the time on investigational and reference treatment.
Results:
There were multiple scenarios in which two solutions were found: one corresponding to identical counterfactual distributions, and the other to two different crossing counterfactual distributions. The same was found for the hazard ratio (HR). Unique solutions were observed only when switching patients were on investigational treatment for <40% of the time that patients in the investigational arm were on treatment.
Limitations:
Distributions other than exponential could have been used for time on treatment.
Conclusions:
An HR equal to 1 is a necessary but not always sufficient condition to indicate acceleration factors associated with equal counterfactual survival. Further assessment to distinguish crossing counterfactual curves from equal counterfactual curves is especially needed when the time that switchers stay on investigational treatment is relatively long compared to the time direct starters stay on investigational treatment.
Purpose:
Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time-varying exposure and confounding in pharmacoepidemiology and other observational studies. The methods are explored from a conceptual rather than an analytical perspective.
Methods:
The methods described in this study have been identified exploring the literature concerning to the time-varying exposure concept and basing the search on four fundamental pharmacoepidemiological problems, construction of treatment episodes, time-varying confounders, cumulative exposure and latency, and treatment switching.
Results:
A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time-varying covariates, but the complexity of the most advanced approaches-eg, marginal structural models or structural nested failure time models-and the lack of user-friendly statistical packages have prevented broader adoption of these methods. Consequently, simpler methods are most commonly used, including, for example, methods without any adjustment strategy and models with time-varying covariates. The magnitude of exposure needs to be considered and properly modelled.
Conclusions:
Further research on the application and implementation of the most complex methods is needed. Because different methods can lead to substantial differences in the treatment effect estimates, the application of several methods and comparison of the results is recommended. Treatment episodes estimation and exposure quantification are key parts in the estimation of treatment effects or associations of interest.
Molecularly targeted anti-cancer therapies have revolutionized cancer treatment by improving both quality of life and survival in cancer patients. However, many of these drugs are associated with cardiovascular toxicities that are sometimes dose-limiting. Moreover, the long-term cardiovascular consequences of these drugs, some of which are used chronically, are not yet known. Although the scope and mechanisms of the cardiac toxicities are better defined, the mechanisms for vascular toxicities are only beginning to be elucidated. This review summarizes what is known about the vascular adverse events associated with three classes of novel anti-cancer therapies: vascular endothelial growth factor (VEGF) inhibitors, breakpoint cluster-Abelson (BCR-ABL) kinase inhibitors used to treat chronic myelogenous leukaemia (CML) and immunomodulatory agents (IMiDs) used in myeloma therapeutics. Three of the best described vascular toxicities are reviewed including hypertension, increased risk of acute cardiovascular ischaemic events and arteriovenous thrombosis. The available data regarding the mechanism by which each therapy causes vascular complication are summarized. When data are limited, potential mechanisms are inferred from the known effects of inhibiting each target on vascular cell function and disease. Enhanced understanding of the molecular mechanisms of vascular side effects of targeted cancer therapy is necessary to effectively manage cancer patients and to design safer targeted cancer therapies for the future.
Background:
Offering patients in oncology trials the opportunity to cross over to active treatment at disease progression is a common strategy to address ethical issues associated with placebo controls but may lead to statistical challenges in the analysis of overall survival and cost-effectiveness because crossover leads to information loss and dilution of comparative clinical efficacy.
Objectives:
We provide an overview of how to address crossover, implications for risk-effect estimates of survival (hazard ratios) and cost-effectiveness, and how this influences decisions of reimbursement agencies. Two case studies using data from two phase III sunitinib oncology trials are used as illustration.
Methods:
We reviewed the literature on statistical methods for adjusting for crossover and recent health technology assessment decisions in oncology.
Results:
We show that for a trial with a high proportion of crossover from the control arm to the investigational arm, the choice of the statistical method greatly affects treatment-effect estimates and cost-effectiveness because the range of relative mortality risk for active treatment versus control is broad. With relatively frequent crossover, one should consider either the inverse probability of censoring weighting or the rank-preserving structural failure time model to minimize potential bias, with choice dependent on crossover characteristics, trial size, and available data. A large proportion of crossover favors the rank-preserving structural failure time model, while large sample size and abundant information about confounding factors favors the inverse probability of censoring weighting model. When crossover is very infrequent, methods yield similar results.
Conclusions:
Failure to correct for crossover may lead to suboptimal decisions by pricing and reimbursement authorities, thereby limiting an effective drug's potential.
The National Institute for Health and Clinical Excellence (NICE) invited the manufacturer of pazopanib hydrochloride (GlaxoSmithKline) to submit evidence of the clinical and cost effectiveness of the drug for the first-line treatment of advanced and/or metastatic renal cell carcinoma, as part of the Institute's single technology appraisal (STA) process. The Aberdeen Health Technology Assessment Group were commissioned to act as the Evidence Review Group (ERG). This article provides a description of the company submission, the ERG review and NICE's subsequent decisions. The objective of this paper is to summarize the independent review and critique of the evidence submitted for the consideration of the NICE Appraisal Committee and NICE's subsequently issued guidance. The ERG produced a critical review of the evidence for the clinical and cost effectiveness of the technology based upon the manufacturer's submission to NICE. The ERG also independently searched for relevant evidence and modified the manufacturer's decision analytic model to examine the impact of altering some of the key assumptions. For progression-free survival (PFS), there was a statistically significant longer survival for pazopanib compared with placebo (as assessed by the ERG, based upon the original manufacturer submission with a clinical cut-off date of 23 May 2008) [median 11.1 vs. 2.8 months; hazard ratio (HR) 0.40; 95 % CI 0.27, 0.60]. Data from the indirect comparison suggested that pazopanib had a greater survival than interferon alpha (IFN-α) [HR 0.512; 95 % CI 0.326, 0.802] but provided no evidence of any difference compared with sunitinib (HR 0.949; 95 % CI 0.575, 1.568). With regard to overall survival, 64 % (n = 99) of patients in the pazopanib arm and 63 % (n = 49) of patients in the placebo arm had died and a total of 51 % (n = 40) of placebo patients had crossed over to receive pazopanib. Although data were provided on an intention-to-treat basis, crossover between therapies made such data difficult to interpret. There was no evidence of any statistically significant difference between pazopanib and best supportive care (HR 0.501; 95 % CI 0.136, 2.348). In the indirect comparison, there were no statistically significant differences between pazopanib and IFN-α (HR 0.627; 95 % CI 0.173, 2.269) or between pazopanib and sunitinib (HR 0.969; 95 % CI 0.359, 2.608). Based upon the work presented including a 12.5 % discount for pazopanib, sunitinib was extendedly dominated by a combination of pazopanib and IFN-α. As a consequence, the incremental cost per QALY for pazopanib versus IFN-α was £38,925. The results were not greatly altered over the range of univariate deterministic sensitivity analyses conducted by the manufacturer but pair-wise probabilistic sensitivity analyses suggested that given a threshold value of £30,000, there is a 54 % probability that pazopanib was preferred to sunitinib, 40 % chance against IFN-α and 47 % chance against best supportive care. The Appraisal Committee concluded that pazopanib should be recommended as a first-line treatment option for people with advanced renal cell carcinoma who have not received prior cytokine therapy and have an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, and if the manufacturer provides pazopanib with a 12.5 % discount on the list price and provides a possible future rebate linked to the outcome of the head-to-head COMPARZ trial, as agreed under the terms of the patient access scheme and to be confirmed when the COMPARZ trial data are made available.
Ideally, therapeutic interventions are evaluated through randomized clinical trials. These trials are commonly analyzed with an intent-to-treat (ITT) approach, whereby patients are analyzed in their assigned treatment group regardless of actual treatment received. If an interim analysis of such trials demonstrates compelling evidence of a difference in benefit, ethical considerations often dictate that the trial be unblinded and participants be provided access to the more efficacious agent. Because interim analysis may not address longer-term outcomes of interest, important clinical questions such as overall survival benefit-the ultimate test of efficacy to many-may remain unanswered. The ensuing crossover disturbs randomization and may lead to biased longer-term analysis, compromising the utility of clinical data. This has been especially apparent in recent adjuvant and prevention breast cancer trials. We consider four such trials: HERA (Herceptin Adjuvant), NSABP P-1 (National Surgical Adjuvant Breast and Bowel Project Breast Cancer Prevention P-1), MA.17, and BIG 1-98 (Breast International Group 1-98), the long-term outcomes of which were complicated by unblinding and selective crossover. We also discuss the biases associated with ITT analysis and, alternatively, censoring of follow-up data (ie, dropping out) after selective crossover. Moreover, we discuss how the statistical procedure of inverse probability of censoring weighted (IPCW) analysis may be used to account for selective crossover as an alternative to ITT or censoring analysis, as was recently done for the BIG 1-98 trial. Notably, IPCW analysis may be particularly suited for detecting overall survival benefits that otherwise would not be detected with an ITT approach, as reported for the BIG 1-98 trial.
Randomized controlled trials often suffer from two major complications, i.e., noncompliance and missing outcomes. One potential solution to this problem is a statistical concept called intention-to-treat (ITT) analysis. ITT analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization. ITT analysis maintains prognostic balance generated from the original random treatment allocation. In ITT analysis, estimate of treatment effect is generally conservative. A better application of the ITT approach is possible if complete outcome data are available for all randomized subjects. Per-protocol population is defined as a subset of the ITT population who completed the study without any major protocol violations.
In time-to-event analyses, artificial censoring with correction for induced selection bias using inverse probability-of-censoring weights can be used to 1) examine the natural history of a disease after effective interventions are widely available, 2) correct bias due to noncompliance with fixed or dynamic treatment regimens, and 3) estimate survival in the presence of competing risks. Artificial censoring entails censoring participants when they meet a predefined study criterion, such as exposure to an intervention, failure to comply, or the occurrence of a competing outcome. Inverse probability-of-censoring weights use measured common predictors of the artificial censoring mechanism and the outcome of interest to determine what the survival experience of the artificially censored participants would be had they never been exposed to the intervention, complied with their treatment regimen, or not developed the competing outcome. Even if all common predictors are appropriately measured and taken into account, in the context of small sample size and strong selection bias, inverse probability-of-censoring weights could fail because of violations in assumptions necessary to correct selection bias. The authors used an example from the Multicenter AIDS Cohort Study, 1984-2008, regarding estimation of long-term acquired immunodeficiency syndrome-free survival to demonstrate the impact of violations in necessary assumptions. Approaches to improve correction methods are discussed.
We investigate methods used to analyse the results of clinical trials with survival outcomes in which some patients switch from their allocated treatment to another trial treatment. These included simple methods which are commonly used in medical literature and may be subject to selection bias if patients switching are not typical of the population as a whole. Methods which attempt to adjust the estimated treatment effect, either through adjustment to the hazard ratio or via accelerated failure time models, were also considered. A simulation study was conducted to assess the performance of each method in a number of different scenarios.
16 different scenarios were identified which differed by the proportion of patients switching, underlying prognosis of switchers and the size of true treatment effect. 1000 datasets were simulated for each of these and all methods applied. Selection bias was observed in simple methods when the difference in survival between switchers and non-switchers were large. A number of methods, particularly the AFT method of Branson and Whitehead were found to give less biased estimates of the true treatment effect in these situations.
Simple methods are often not appropriate to deal with treatment switching. Alternative approaches such as the Branson & Whitehead method to adjust for switching should be considered.
This paper represents a summary of the evidence review group (ERG) report into the clinical efficacy, safety and cost-effectiveness of everolimus plus best supportive care (BSC) for the treatment of advanced renal cell carcinoma (RCC) which has progressed following or on vascular endothelial growth factor-targeted therapy (sunitinib, sorafenib, bevacizumab), compared to BSC alone. The submitting manufacturer's case for clinical effectiveness and cost-effectiveness was mainly based on a well-conducted randomised controlled trial (RCT), Renal Cell Cancer Treatment with Oral RAD001 Given Daily-1 (RECORD-1), comparing BSC plus everolimus with BSC plus placebo and a de novo economic model. The RCT indicated a marked statistically significant effect on progression-free survival. The base-case incremental cost-effectiveness ratio (ICER) estimate was 52,000 pounds per quality-adjusted life-year (this included a reduction in drug cost associated with an approved patient access scheme). The ERG undertook a critical appraisal of the submission. The ERG was generally in agreement with the submitting manufacturer concerning its estimates of effectiveness; however, there was greater concern surrounding the estimates of cost-effectiveness. The ERG judged that if potential errors in the model were corrected, the ICERs offered by the submitting manufacturer would overstate the cost-effectiveness of everolimus for the second-line treatment of metastatic RCC (that this ICER would be a higher value). Concerning the estimates of cost-effectiveness in RCC, the observations in the ERG report provide strong further support for research collecting rigorous estimates of utilities associated with the main health states likely to be experienced by patients with renal cell cancer. At the time of writing, NICE was yet to issue the Appraisal Consultation Document for this appraisal.
Purpose
Pazopanib is an oral angiogenesis inhibitor targeting vascular endothelial growth factor receptor, platelet-derived growth factor receptor, and c-Kit. This randomized, double-blind, placebo-controlled phase III study evaluated efficacy and safety of pazopanib monotherapy in treatment-naive and cytokine-pretreated patients with advanced renal cell carcinoma (RCC).
Patients and Methods
Adult patients with measurable, locally advanced, and/or metastatic RCC were randomly assigned 2:1 to receive oral pazopanib or placebo. The primary end point was progression-free survival (PFS). Secondary end points included overall survival, tumor response rate (Response Evaluation Criteria in Solid Tumors), and safety. Radiographic assessments of tumors were independently reviewed.
Results
Of 435 patients enrolled, 233 were treatment naive (54%) and 202 were cytokine pretreated (46%). PFS was significantly prolonged with pazopanib compared with placebo in the overall study population (median, PFS 9.2 v 4.2 months; hazard ratio [HR], 0.46; 95% CI, 0.34 to 0.62; P < .0001), the treatment-naive subpopulation (median PFS 11.1 v 2.8 months; HR, 0.40; 95% CI, 0.27 to 0.60; P < .0001), and the cytokine-pretreated subpopulation (median PFS, 7.4 v 4.2 months; HR, 0.54; 95% CI, 0.35 to 0.84; P < .001). The objective response rate was 30% with pazopanib compared with 3% with placebo (P < .001). The median duration of response was longer than 1 year. The most common adverse events were diarrhea, hypertension, hair color changes, nausea, anorexia, and vomiting. There was no evidence of clinically important differences in quality of life for pazopanib versus placebo.
Conclusion
Pazopanib demonstrated significant improvement in PFS and tumor response compared with placebo in treatment-naive and cytokine-pretreated patients with advanced and/or metastatic RCC.
The spiraling cost of cancer care, in particular the cost of cancer therapeutics that achieve only marginal benefits, is under
increasing scrutiny. Although health-care professionals avoid putting a value on a life, our limited resources require that
society address what counts as a benefit, the extent to which cost should factor in deliberations, and who should be involved
in these decisions. Professional societies, such as the American Society of Clinical Oncology, government agencies, including
the Food and Drug Administration, and insurance companies should be involved. However, no segment of society is better qualified
to address these issues than the oncology community. Oncologists must offer clear guidance for the conduct of research, interpretation
of results, and prescription of chemotherapies. We review recent drug approvals and clinical trials and comment on their relevance
to the issue of the spiraling cost of oncology therapeutics. We suggest some standards that would serve as a starting point
for addressing these issues.
A randomized, phase III trial demonstrated superiority of sunitinib over interferon alfa (IFN-alpha) in progression-free survival (primary end point) as first-line treatment for metastatic renal cell carcinoma (RCC). Final survival analyses and updated results are reported.
Seven hundred fifty treatment-naïve patients with metastatic clear cell RCC were randomly assigned to sunitinib 50 mg orally once daily on a 4 weeks on, 2 weeks off dosing schedule or to IFN-alpha 9 MU subcutaneously thrice weekly. Overall survival was compared by two-sided log-rank and Wilcoxon tests. Progression-free survival, response, and safety end points were assessed with updated follow-up.
Median overall survival was greater in the sunitinib group than in the IFN-alpha group (26.4 v 21.8 months, respectively; hazard ratio [HR] = 0.821; 95% CI, 0.673 to 1.001; P = .051) per the primary analysis of unstratified log-rank test (P = .013 per unstratified Wilcoxon test). By stratified log-rank test, the HR was 0.818 (95% CI, 0.669 to 0.999; P = .049). Within the IFN-alpha group, 33% of patients received sunitinib, and 32% received other vascular endothelial growth factor-signaling inhibitors after discontinuation from the trial. Median progression-free survival was 11 months for sunitinib compared with 5 months for IFN-alpha (P < .001). Objective response rate was 47% for sunitinib compared with 12% for IFN-alpha (P < .001). The most commonly reported sunitinib-related grade 3 adverse events included hypertension (12%), fatigue (11%), diarrhea (9%), and hand-foot syndrome (9%).
Sunitinib demonstrates longer overall survival compared with IFN-alpha plus improvement in response and progression-free survival in the first-line treatment of patients with metastatic RCC. The overall survival highlights an improved prognosis in patients with RCC in the era of targeted therapy.
In a randomized study of advanced renal cell carcinoma 60 patients were allocated to treatment with either recombinant interferon alpha-2a or medroxyprogesterone acetate. Correlation between the dose of interferon alpha-2a and plasma-concentration indicated linear kinetics. Survival was similar in the two treatment groups. Only one complete and one partial response were seen in the interferon group and only one complete response in the medroxyprogesterone group, indicating a low therapeutic potential of both interferon and medroxyprogesterone. Interferon influenced the serum liver enzyme levels; increased transaminases were seen in 17 patients treated with interferon but in only four patients in the medroxyprogesterone group. Two patients had very high serum liver-enzyme levels concomitant with intolerable tiredness, in both patients the symptoms disappeared and the enzymes normalized after discontinuation of the interferon treatment. Antibodies to interferon developed frequently in patients receiving high dose oligomeric interferon therapy but rarely in patients receiving low dose monomeric interferon treatment.
Clinical research to improve breast cancer treatment has produced multiple, meaningful advances in the last decade. New antiestrogen and chemotherapeutic agents—novel therapies directed towards HER2—such as trastuzumab and lapatinib, and antiangiogenic agents, such as bevacizumab, have all been added to the clinician’s armamentarium to treat metastatic disease. 1 Several of these advances have now demonstrated efficacy in the adjuvant setting, which raises the important question: What exactly has improved as these agents have been introduced into the metastatic setting? Given the current limited possibility of cure for these patients, there are two clinically important goals of treatment: make the patient live longer and delay or relieve symptoms. The first of these end points, codified as overall survival (OS), is simple to measure, unambiguous, and of unquestionable clinical relevance. However, symptom relief and palliation (or quality of life), despite recent progress, is notoriously difficult to measure. 2 Ideally, a newly introduced antineoplastic agent will demonstrate a significant and clinically meaningful prolongation of overall survival in the setting of a randomized controlled trial. However, the use of overall survival as the primary end point for a clinical trial has several major drawbacks. First, because mortality occurs after a relatively long time for most patients, statistically significant differences in OS require large numbers of patients and several years to reliably detect. For example, in a recently reported trial in which women with metastatic breast cancer were randomly assigned to receive either bevacizumab or no bevacizumab, in addition to first-line paclitaxel, the median survival for the trial population was not reached until nearly 8 years after the trial was opened, a full 2 years after initial results (based on an end point of progression-free survival [PFS]) were made public. 3 Second, for many new agents, patients assigned to the control arm are either allowed to cross over to the investigational agent or to receive the investigational agent off-study on disease progression. This strategy dilutes effects of an agent on OS, since patients in both arms will receive the new agent at some point. Although a prohibition of such cross-over is scientifically appealing, ethical considerations often preclude it, particularly if outcomes on earlier end points are found to be promising or the drug is approved in later line settings. Finally, for addition of a new agent, a prolongation of OS may be more difficult to detect now than in the past due to the beneficial effects of the many other antineoplastic therapies now available for breast cancer. 1
Background
The adequacy of overall survival (OS) as study end point in phase III trials for advanced solid tumors is questionable. The present review highlights the limits of OS as study end point to evaluate the efficacy of new drugs.
Methods
Four phase III clinical trials comparing a fluorouracil-based regimen with the same regimen plus either CPT-11 or oxaliplatin in advanced colorectal cancer patients were reviewed. The primary aim of the critical assessment was to explain the lack of OS advantage observed in two of the four trials, despite the presence of increased response rate (RR) and time to progression (TTP). Four possible reasons for the lack of OS benefit (i.e. statistical power, cross-over, magnitude of the effect on RR and TTP, non-tumor-related deaths) were systematically reviewed in the trials, and the detectable 1-year OS difference, assuming a statistical power of 80%, was calculated for each.
Results
None of these reasons for the lack of OS advantage in presence of RR and TTP benefits convincingly explained the results of the evaluated trials. Three of the four trials had roughly the same statistical power to detect 1-year OS differences, while the fourth trial was underpowered to detect realistic OS differences. The lack of OS advantage observed in the two oxaliplatin trials is therefore likely fortuitous, and due to lack of statistical power.
Conclusions
Although increase in OS remains the ultimate goal of many clinical trials, the choice of OS benefit as a mandatory requirement to register new compounds can lead to a serious underestimation of a drug’s real efficacy.
Estimates of the overall survival benefit of new cancer treatments are often confounded by treatment switching in randomised controlled trials (RCTs) - whereby patients randomised to the control group are permitted to switch onto the experimental treatment upon disease progression. In health technology assessment, estimates of the unconfounded overall survival benefit associated with the new treatment are needed. Several switching adjustment methods have been advocated in the literature, some of which have been used in health technology assessment. However, it is unclear which methods are likely to produce least bias in realistic RCT-based scenarios. We simulated RCTs in which switching, associated with patient prognosis, was permitted. Treatment effect size and time dependency, switching proportions and disease severity were varied across scenarios. We assessed the performance of alternative adjustment methods based upon bias, coverage and mean squared error, related to the estimation of true restricted mean survival in the absence of switching in the control group. We found that when the treatment effect was not time-dependent, rank preserving structural failure time models (RPSFTM) and iterative parameter estimation methods produced low levels of bias. However, in the presence of a time-dependent treatment effect, these methods produced higher levels of bias, similar to those produced by an inverse probability of censoring weights method. The inverse probability of censoring weights and structural nested models produced high levels of bias when switching proportions exceeded 85%. A simplified two-stage Weibull method produced low bias across all scenarios and provided the treatment switching mechanism is suitable, represents an appropriate adjustment method.
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Treatment switching commonly occurs in clinical trials of novel interventions in the advanced or metastatic cancer setting. However, methods to adjust for switching have been used inconsistently and potentially inappropriately in health technology assessments (HTAs).
. We present recommendations on the use of methods to adjust survival estimates in the presence of treatment switching in the context of economic evaluations.
. We provide background on the treatment switching issue and summarize methods used to adjust for it in HTAs. We discuss the assumptions and limitations associated with adjustment methods and draw on results of a simulation study to make recommendations on their use.
. We demonstrate that methods used to adjust for treatment switching have important limitations and often produce bias in realistic scenarios. We present an analysis framework that aims to increase the probability that suitable adjustment methods can be identified on a case-by-case basis. We recommend that the characteristics of clinical trials, and the treatment switching mechanism observed within them, should be considered alongside the key assumptions of the adjustment methods. Key assumptions include the "no unmeasured confounders" assumption associated with the inverse probability of censoring weights (IPCW) method and the "common treatment effect" assumption associated with the rank preserving structural failure time model (RPSFTM).
. The limitations associated with switching adjustment methods such as the RPSFTM and IPCW mean that they are appropriate in different scenarios. In some scenarios, both methods may be prone to bias; "2-stage" methods should be considered, and intention-to-treat analyses may sometimes produce the least bias. The data requirements of adjustment methods also have important implications for clinical trialists.
Background:
Pazopanib and sunitinib provided a progression-free survival benefit, as compared with placebo or interferon, in previous phase 3 studies involving patients with metastatic renal-cell carcinoma. This phase 3, randomized trial compared the efficacy and safety of pazopanib and sunitinib as first-line therapy.
Methods:
We randomly assigned 1110 patients with clear-cell, metastatic renal-cell carcinoma, in a 1:1 ratio, to receive a continuous dose of pazopanib (800 mg once daily; 557 patients) or sunitinib in 6-week cycles (50 mg once daily for 4 weeks, followed by 2 weeks without treatment; 553 patients). The primary end point was progression-free survival as assessed by independent review, and the study was powered to show the noninferiority of pazopanib versus sunitinib. Secondary end points included overall survival, safety, and quality of life.
Results:
Pazopanib was noninferior to sunitinib with respect to progression-free survival (hazard ratio for progression of disease or death from any cause, 1.05; 95% confidence interval [CI], 0.90 to 1.22), meeting the predefined noninferiority margin (upper bound of the 95% confidence interval, <1.25). Overall survival was similar (hazard ratio for death with pazopanib, 0.91; 95% CI, 0.76 to 1.08). Patients treated with sunitinib, as compared with those treated with pazopanib, had a higher incidence of fatigue (63% vs. 55%), the hand-foot syndrome (50% vs. 29%), and thrombocytopenia (78% vs. 41%); patients treated with pazopanib had a higher incidence of increased levels of alanine aminotransferase (60%, vs. 43% with sunitinib). The mean change from baseline in 11 of 14 health-related quality-of-life domains, particularly those related to fatigue or soreness in the mouth, throat, hands, or feet, during the first 6 months of treatment favored pazopanib (P<0.05 for all 11 comparisons).
Conclusions:
Pazopanib and sunitinib have similar efficacy, but the safety and quality-of-life profiles favor pazopanib. (Funded by GlaxoSmithKline Pharmaceuticals; COMPARZ ClinicalTrials.gov number, NCT00720941.).
We review how overall survival (OS) comparisons should be interpreted with increasing availability of effective therapies that can be given subsequently to the treatment assigned in a randomized clinical trial (RCT). We examine in detail how effective subsequent therapies influence OS comparisons under varying conditions in RCTs. A subsequent therapy given after tumor progression (or relapse) in an RCT that works better in the standard arm than the experimental arm will lead to a smaller OS difference (possibly no difference) than one would see if the subsequent therapy was not available. Subsequent treatments that are equally effective in the treatment arms would not be expected to affect the absolute OS benefit of the experimental treatment but will make the relative improvement in OS smaller. In trials in which control arm patients cross over to the experimental treatment after their condition worsens, a smaller OS difference could be observed than one would see without cross-overs. In particular, use of cross-over designs in the first definitive evaluation of a new agent in a given disease compromises the ability to assess clinical benefit. In disease settings in which there is not an intermediate end point that directly measures clinical benefit, OS should be the primary end point of an RCT. The observed difference in OS should be considered the measure of clinical benefit to the patients, regardless of subsequent therapies, provided that the subsequent therapies used in both treatment arms follow the current standard of care.
The United States leads the world in cancer care outcomes, but the cost is extremely high-and growing rapidly. New proposals for health reform emphasize one clear and immediate need: to control runaway cost.
The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection bias under the four assumptions of consistency, exchangeability, positivity, and no misspecification of the model used to estimate weights. In recent years, several published estimates of the effect of time-varying exposures have been based on weighted estimation of the parameters of marginal structural models because, unlike standard statistical methods, weighting can appropriately adjust for measured time-varying confounders affected by prior exposure. As an example, the authors describe the last three assumptions using the change in viral load due to initiation of antiretroviral therapy among 918 human immunodeficiency virus-infected US men and women followed for a median of 5.8 years between 1996 and 2005. The authors describe possible tradeoffs that an epidemiologist may encounter when attempting to make inferences. For instance, a tradeoff between bias and precision is illustrated as a function of the extent to which confounding is controlled. Weight truncation is presented as an informal and easily implemented method to deal with these tradeoffs. Inverse probability weighting provides a powerful methodological tool that may uncover causal effects of exposures that are otherwise obscured. However, as with all methods, diagnostics and sensitivity analyses are essential for proper use.
Since the beginning of the 1980s, when gene technology provided sufficient amounts of cytokines, numerous Phase II studies in metastatic renal cell carcinoma were carried out mostly with interferon alfa (IFN-alpha) and interleukin-2 (IL-2). So far, no randomized prospective trials including untreated control groups have been reported. We present a prospective study comparing IFN-alpha and vinblastine (VBL) versus medroxyprogesterone acetate (MPA).
Immunochemotherapy schedule consists of IFN-alpha 8 million U/day subcutaneously for 3 days per week and VBL 0.1 mg/kg body weight intravenously at 3-week intervals. MPA was administrated intramuscularly at a dosage of 500 mg/week. The response rates, toxicities, and actuarial overall survival were analyzed.
The overall response rate in 41 patients receiving IFN-alpha and VBL treatment was 20.5% (95% confidence interval, 9% to 33%). Four patients reached a complete and 5 patients reached a partial remission. No remissions were observed in 35 patients of the control group. A statistically significant survival benefit for the IFN-alpha and VBL group could not be demonstrated. Excluding fever, mild to moderate toxicities were observed. About one third of patients refused the proposed schedule due to general malaise and fatigue.
A survival benefit or a favorable outcome of patients with metastatic renal cell carcinoma, treated with IFN-alpha and VBL, could not be demonstrated. As judged from this analysis, IFN-alpha and VBL therapy does not sufficiently meet the requirements of a palliative treatment of renal cell carcinoma.
The combination of interferon alfa-2a (IFNalpha2a) plus vinblastine (VLB) induces objective tumor responses in patients with advanced renal cell cancer. However, no prospective randomized trial has shown that this treatment prolongs overall survival. We compared overall survival after treatment with IFNalpha2a plus VLB versus VLB alone in patients with advanced renal cell cancer.
We prospectively randomized 160 patients with locally advanced or metastatic renal cell cancer to receive either VLB alone or IFNalpha2a plus VLB for 12 months or until progression of disease. In both groups, VLB was administered intravenously at 0.1 mg/kg every 3 weeks, and in the combination group IFNalpha2a was administered subcutaneously at 3 million units three times a week for 1 week, and 18 million units three times a week thereafter for the second and subsequent weeks. For patients unable totolerate IFNalpha2a at 18 million units per injection, the dose was reduced to 9 million units.
Median survival was 67.6 weeks for the 79 patients receiving IFNalpha2a plus VLB and 37.8 weeks for the 81 patients treated with VLB (P =.0049). Overall response rates were 16. 5% for patients treated with IFNalpha2a plus VLB and 2.5% for patients treated with VLB alone (P =.0025). Treatment with the combination was associated with constitutional symptoms and abnormalities in laboratory parameters, but no toxic deaths were reported.
The combination of IFNalpha2a plus VLB is superior to VLB alone in the treatment of patients with locally advanced or metastatic renal cell carcinoma. This is the first study to demonstrate that survival can be prolonged by using IFNalpha2a for these patients.
The adequacy of overall survival (OS) as study end point in phase III trials for advanced solid tumors is questionable. The present review highlights the limits of OS as study end point to evaluate the efficacy of new drugs.
Four phase III clinical trials comparing a fluorouracil-based regimen with the same regimen plus either CPT-11 or oxaliplatin in advanced colorectal cancer patients were reviewed. The primary aim of the critical assessment was to explain the lack of OS advantage observed in two of the four trials, despite the presence of increased response rate (RR) and time to progression (TTP). Four possible reasons for the lack of OS benefit (i.e. statistical power, cross-over, magnitude of the effect on RR and TTP, non-tumor-related deaths) were systematically reviewed in the trials, and the detectable 1-year OS difference, assuming a statistical power of 80%, was calculated for each.
None of these reasons for the lack of OS advantage in presence of RR and TTP benefits convincingly explained the results of the evaluated trials. Three of the four trials had roughly the same statistical power to detect 1-year OS differences, while the fourth trial was underpowered to detect realistic OS differences. The lack of OS advantage observed in the two oxaliplatin trials is therefore likely fortuitous, and due to lack of statistical power.
Although increase in OS remains the ultimate goal of many clinical trials, the choice of OS benefit as a mandatory requirement to register new compounds can lead to a serious underestimation of a drug's real efficacy.
Cost-effectiveness analysis may be applied to the full range of interventions that make up a cancer service, including screening programmes and early treatments, diagnostic test and referral processes, surgery, radiotherapy, chemotherapy and palliative care. Numerous methodologies have been employed within existing models of cancer interventions. However, not all methodologies are equal; inappropriate modelling approaches may bias cost-effectiveness results. Generic guidelines for good practice in decision-analytic modelling provide a useful basis for critically appraising cost-effectiveness models, yet explicit consideration of a range of cancer-specific issues is required to avoid bias in cost-effectiveness results. These cancer-specific issues include the appropriate representation of relevant costs and health effects associated with unplanned treatments for metastatic disease administered beyond disease progression, the appropriate extrapolation of long-term outcomes and resources from clinical trials, assumptions concerning the nature of the event hazard function beyond the duration of the trial, and relationships between surrogate outcomes and final outcomes.
Few randomized trials have compared the survival benefit of interferon-alfa over controls in metastatic renal cell carcinoma, and none has been performed using interleukin-2. The Programme Etude Rein Cytokines (PERCY) Quattro trial was designed to evaluate both cytokines for their survival benefit to intermediate prognosis patients, who represent the majority of candidates for these treatments.
Patients were randomized in a 2-by-2 factorial design to medroxyprogesterone acetate 200 mg daily, interferon-alfa 9 million IU 3 times a week, subcutaneous interleukin-2 9 million IU daily, or a combination of both cytokines. Tumor response was evaluated at Week 12 and Month 6; progression-free patients received further identical treatment for a maximum of 3 additional months. Primary endpoint was overall survival; secondary endpoints were disease-free survival, response rate, toxicity, and quality of life. Survival was analyzed on an intent-to-treat basis.
From January 2000 to July 2004, 492 patients were enrolled. Analysis was performed after a 29.2-month median follow-up (range, 0 months to 54.6 months). There were no significant survival differences between the 244 interferon-alfa-treated patients and 248 noninterferon-alfa patients (hazard ratio, 1.00; 95% CI, 0.81-1.24) or between the 247 interleukin-2 and 245 noninterleukin-2-treated patients (hazard ratio, 1.07; 95% CI, 0.87-1.33; log rank, 0.99 and 0.52, respectively). Grade 3-4 toxicities were significantly more frequent in cytokine-treated patients than in medroxyprogesterone-treated patients.
Subcutaneous interleukin-2 and/or interferon-alfa provide no survival benefit in metastatic renal cancers of intermediate prognosis, and they induce a significant risk of toxicity. Newly available angiogenesis inhibitors should be preferred for these patients.
To examine the ethical, scientific, and regulatory issues in the design and conduct of placebo-controlled cancer clinical trials.
Several content experts contributed to this article.
Specific criteria can be applied to determine the appropriate use of placebos in oncology drug development. Placebo controls may be justified to prove efficacy of a new treatment in diseases with high placebo response rates; in conditions that wax and wane in severity, have spontaneous remissions, or have an uncertain and unpredictable course; when existing therapies are minimally effective or have serious adverse effects; or in the absence of effective therapy. Use of placebos may also be justified to assure blinding of physicians and patients regarding treatment assignment so as to minimize bias in assessment of study end points. If a trial meets these methodologic criteria, it must then fulfill additional criteria to be considered ethical. These criteria include full disclosure to patients and an assurance that participants randomly assigned to placebo are not substantially more likely than those in active treatment group(s) to die; suffer irreversible morbidity, disability, or other substantial harms; suffer reversible but serious harm; or suffer severe discomfort.
We conclude that placebo-controlled oncology trials are scientifically feasible, ethically justifiable, and may be necessary or desirable to meet regulatory standards for drug approval. Using cross-over or randomized withdrawal trial designs, requiring inclusion of state-of-the-art palliative care, and developing valid and acceptable surrogates for survival are critical strategies to address some of the ethical dilemmas associated with placebo-controlled trials.
Advanced renal cell carcinoma has been resistant to drug therapy of different types and new types of drug therapy are needed. Targeted agents inhibit known molecular pathways involved in cellular proliferation and neoangiogenesis, the induction by the tumour of host microvascular networks. Angiogenesis is of special interest in the clear cell histologic subtype of renal cancer because of its vascularity and constitutively activated hypoxia-inducible path in the majority of tumours.
1) To provide a systematic review of studies testing targeted agents.2) To identify the type and degree of clinical benefit, if any, of targeted agents over the prior standard of care, particularly any impact on overall survival.
1) Electronic search of CENTRAL, MEDLINE and EMBASE databases.2) Hand search of international cancer meeting abstract and other sources specified in the protocol.
Randomized controlled studies of targeted agents in patients with advanced renal cell cancer reporting major remission rate or overall survival by allocation. Progression-free survival (PFS) was adopted as an additional outcome because PFS was a commonly chosen primary outcome, and because several pivotal studies allowed crossover from the control to the investigational arm after closure to accrual thereby making overall survival a problematic endpoint.
Nineteen fully eligible studies tested ten different targeted agents (Table 04). One additional study was excluded because no outcome data by allocation have been reported (Hutson 2007). For purposes of comparison, the studies were divided into three groups: Group 1 studies compared different doses of the same agents; Group 2 studies examined the impact of targeted agents in patients who had received prior cytokine or other systemic therapy; and Group 3 studies tested targeted agents in systemically naive patients, either against standard interferon-alfa or against another control therapy. Meta-analysis was not utilized because there were very few situations where the same agents had been tested in the same group in more than one study.
In systemically untreated patients in studies using subcutaneous interferon-alfa as control therapy, the major findings were: 1) An improvement in overall survival has been demonstrated only with the use of weekly intravenous temsirolimus in patients with unselected renal cancer histology and adverse prognostic features (median survival 10.9 months versus 7.3 months for temsirolimus or interferon-alfa respectively, HR 0.73, P = 0.008 log rank, Hudes 2007). However, the chance of major remission was low and not improved with temsirolimus. 2) In patients with mostly good or intermediate prognostic risk with clear cell renal cancer, oral sunitinib improves the chance of major remission, the probability of symptomatic improvement, and freedom from disease progression (Motzer 2007); in a similar setting, the addition of biweekly intravenous bevacizumab to interferon-alfa also improved the chance of major remission and prolonged progression-free survival (Escudier 2007b); overall survival had not changed at the time of interim reporting of either study. In patients with clear cell renal cancers who had failed prior cytokine therapy, oral sorafenib gives a better quality of life than placebo as well as improved chance of being free of disease progression; overall survival may have improved but is hard to evaluate because of crossover of placebo-assigned patients after the study closed to accrual (Escudier 2007a).
Based on less than a decade of experience, some targeted agents with specified molecular targets have demonstrated clinically useful benefits over the previous standard of care for patients with advanced renal cancer. Much more research is required to fully establish the role of targeted agents in this condition.
Medroxyprogesterone, interferon alfa-2a, interleukin 2, or combination of both cytokines in patients with metastatic renal carcinoma of intermediate prognosis: results of a randomized controlled trial
French Immunotherapy Intergroup: Medroxyprogesterone, interferon alfa-2a, interleukin 2, or combination of both cytokines in
patients with metastatic renal carcinoma of
intermediate prognosis: results of a randomized controlled trial. Cancer 2007; 110: 2468-2477.