The phase II/III transition. Toward the proof of efficacy in cancer clinical trials

Exploiting Nanomedicine for Cancer Polychemotherapy: Recent Advances and Clinical Applications

The most important limitations of chemotherapeutic agents are severe side effects and the development of multi-drug resistance. Recently, the clinical successes achieved with immunotherapy have revolutionized the treatment of several advanced-stage malignancies, but most patients do not respond and many of them develop immune-related adverse events. Loading synergistic combinations of different anti-tumor drugs in nanocarriers may enhance their efficacy and reduce life-threatening toxicities. Thereafter, nanomedicines may synergize with pharmacological, immunological, and physical combined treatments, and should be increasingly integrated in multimodal combination therapy regimens. The goal of this manuscript is to provide better understanding and key considerations for developing new combined nanomedicines and nanotheranostics. We will clarify the potential of combined nanomedicine strategies that are designed to target different steps of the cancer growth as well as its microenvironment and immunity interactions. Moreover, we will describe relevant experiments in animal models and discuss issues raised by translation in the human setting.

A new statistical decision rule for single-arm phase II oncology trials

Most single-arm phase II clinical trials compare the efficacy of a new treatment with historical controls through statistical hypothesis testing. One major problem with such a comparison is that the efficacy of the historical control is treated as a known constant, whereas in reality, it is never precisely known. This partially explains why many "Go" decisions made in single-arm phase II trials are shown to be incorrect in phase III trials. In this paper, we propose a new decision rule for an improved transitional decision for single-arm phase II oncology clinical trials with binary endpoints. This new decision rule is jointly based on the p value and a new statistical index named the testing confidence value. The testing confidence value reflects the uncertainty associated with the null value in the hypothesis testing of single-arm trials. Simulations are used to evaluate the operating characteristics of the new decision rule in comparison with the traditional decision rule and a widely used Bayesian decision rule. The application of the new decision rule is illustrated using a clinical trial on marginally resectable pancreatic cancer. A webpage http://www.yiyichenbiostatistics.com/TCV.html is available for readers to interactively compute the testing confidence value and to find the suggested decision based on the new decision rule.

End points and outcomes in castration-resistant prostate cancer: from clinical trials to clinical practice

New therapeutic approaches for castration-resistant prostate cancer (CRPC) introduce new treatment dilemmas: how best to sequence these options to maximally benefit patients, what tests to perform before and after treatment to assess disease status, and how to interpret the test results and use them to guide treatment. New and specific end points for different classes of drugs are needed to provide the information to guide these treatment decisions. In 2008, the Prostate Cancer Working Group 2 consensus criteria for early-phase clinical trials redefined clinical trial end points as first, to control, relieve, or eliminate disease manifestations present when treatment is started and second, to prevent or delay future disease manifestations. Disease manifestations include prostate-specific antigen (PSA), soft-tissue disease (nodes and/or viscera), bone disease (most common site of spread), and symptoms. Recent US Food and Drug Administration (FDA) approvals for CRPC therapies have been based on the prevent/delay end points that reflect unequivocal benefit to a patient: prolongation of life or reduction in skeletal-related events (SREs). For the practicing oncologist, the control/relieve/eliminate outcomes should serve primarily to inform the decision of whether to continue therapy. In this review, we consider individual end points such as PSA, imaging, and patient-reported outcomes in the context of the control/relieve/eliminate and prevent/delay framework. We address the time-to-event end points of metastasis prevention, SRE, time to progression, and overall survival in the context of regulatory approvals. We also discuss circulating tumor cells measured with the CellSearch assay, recently cleared by the FDA for monitoring CRPC.

Effect of a misspecification of response rates on type I and type II errors, in a phase II Simon design

Phase-II trials are a key stage in the clinical development of a new treatment. Their main objective is to provide the required information for a go/no-go decision regarding a subsequent phase-III trial. In single arm phase-II trials, widely used in oncology, this decision relies on the comparison of efficacy outcomes observed in the trial to historical controls. The false positive rate generally accepted in phase-II trials, around 10%, contrasts with the very high attrition rate of new compounds tested in phase-III trials, estimated at about 60%. We assumed that this gap could partly be explained by the misspecification of the response rate expected with standard treatment, leading to erroneous hypotheses tested in the phase-II trial. We computed the false positive probability of a defined design under various hypotheses of expected efficacy probability. Similarly we calculated the power of the trial to detect the efficacy of a new compound for different expected efficacy rates. Calculations were done considering a binary outcome, such as the response rate, with a decision rule based on a Simon two-stage design. When analysing a single-arm phase-II trial, based on a design with a pre-specified null hypothesis, a 5% absolute error in the expected response rate leads to a false positive rate of about 30% when it is supposed to be 10%. This inflation of type-I error varies only slightly according to the hypotheses of the initial design. Single-arm phase-II trials poorly control for the false positive rate. Randomised phase-II trials should, therefore, be more often considered.

Shortcomings in the clinical evaluation of new drugs: acute myeloid leukemia as paradigm

Drugs introduced over the past 25 years have benefitted many patients with acute myeloid leukemia (AML) and provided cure for some. Still, AML remains difficult to treat, and most patients will eventually die from their disease. Therefore, novel drugs and drug combinations are under intense investigation, and promising results eagerly awaited and embraced. However, drug development is lengthy and costs are staggering. While the phase 1-phase 2-phase 3 sequence of clinical drug testing has remained inviolate for decades, it appears intrinsically inefficient, and scientific flaws have been noted by many authors. Of major concern is the high frequency of false-positive results obtained in phase 2 studies. Here, we review features of phase 2 trials in AML that may contribute to this problem, particularly lack of control groups, patient heterogeneity, selection bias, and choice of end points. Recognizing these problems and challenges should provide us with opportunities to make drug development more efficient and less costly. We also suggest strategies for trial design improvement. Although our focus is on the treatment of AML, the principles that we highlight should be broadly applicable to the evaluation of new treatments for a variety of diseases.

Comparison of error rates in single-arm versus randomized phase II cancer clinical trials

PURPOSE To improve the understanding of the appropriate design of phase II oncology clinical trials, we compared error rates in single-arm, historically controlled and randomized, concurrently controlled designs. PATIENTS AND METHODS We simulated error rates of both designs separately from individual patient data from a large colorectal cancer phase III trials and statistical models, which take into account random and systematic variation in historical control data. RESULTS In single-arm trials, false-positive error rates (type I error) were 2 to 4 times those projected when modest drift or patient selection effects (eg, 5% absolute shift in control response rate) were included in statistical models. The power of single-arm designs simulated using actual data was highly sensitive to the fraction of patients from treatment centers with high versus low patient volumes, the presence of patient selection effects or temporal drift in response rates, and random small-sample variation in historical controls. Increasing sample size did not correct the over optimism of single-arm studies. Randomized two-arm design conformed to planned error rates. CONCLUSION Variability in historical control success rates, outcome drifts in patient populations over time, and/or patient selection effects can result in inaccurate false-positive and false-negative error rates in single-arm designs, but leave performance of the randomized two-arm design largely unaffected at the cost of 2 to 4 times the sample size compared with single-arm designs. Given a large enough patient pool, the randomized phase II designs provide a more accurate decision for screening agents before phase III testing.

Using short-term response information to facilitate adaptive randomization for survival clinical trials

Increased survival is a common goal of cancer clinical trials. Owing to the long periods of observation and follow-up to assess patient survival outcome, it is difficult to use outcome-adaptive randomization in these trials. In practice, often information about a short-term response is quickly available during or shortly after treatment, and this short-term response is a good predictor for long-term survival. For example, complete remission of leukemia can be achieved and measured after a few cycles of treatment. It is a short-term response that is desirable for prolonging survival. We propose a new design for survival trials when such short-term response information is available. We use the short-term information to 'speed up' the adaptation of the randomization procedure. We establish a connection between the short-term response and the long-term survival through a Bayesian model, first by using prior clinical information, and then by dynamically updating the model according to information accumulated in the ongoing trial. Interim monitoring and final decision making are based upon inference on the primary outcome of survival. The new design uses fewer patients, and can more effectively assign patients to the better treatment arms. We demonstrate these properties through simulation studies.

Analysis of Phase II Studies on Targeted Agents and Subsequent Phase III Trials: What Are the Predictors for Success?

Purpose

To identify the characteristics of phase II studies that predict for subsequent “positive” phase III trials (those that reached the proposed primary end points of study or those wherein the study drug was superior to the standard regimen investigating targeted agents in advanced tumors.

Methods

We identified all phase III clinical trials of targeted therapies against advanced cancers published from 1985 to 2005. Characteristics of the preceding phase II studies were reviewed to identify predictive factors for success of the subsequent phase III trial. Data were analyzed using the χ2 test and logistic regression models.

Results

Of 351 phase II studies, 167 (47.6%) subsequent phase III trials were positive and 184 (52.4%) negative. Phase II studies from multiple rather than single institutions were more likely to precede a successful trial (60.4% v 39.4%; P < .001). Positive phase II results were more likely to lead to a successful phase III trial (50.8% v 22.5%; P = .003). The percentage of successful trials from pharmaceutical companies was significantly higher compared with academic, cooperative groups, and research institutes (89.5% v 44.2%, 45.2%, and 46.3%, respectively; P = .002). On multivariate analysis, these factors and shorter time interval between publication of phase II results and III study publication were independent predictive factors for a positive phase III trial.

Conclusion

In phase II studies of targeted agents, multiple- versus single-institution participation, positive phase II trial, pharmaceutical company-based trials, and shorter time period between publication of phase II to phase III trial were independent predictive factors of success in a phase III trial. Investigators should be cognizant of these factors in phase II studies before designing phase III trials.

Design of phase II cancer trials using a continuous endpoint of change in tumor size: application to a study of sorafenib and erlotinib in non small-cell lung cancer

BACKGROUND

The primary objective of phase II cancer clinical trials is to determine whether a new regimen has sufficient activity to warrant further study, with activity generally defined as tumor shrinkage. However, oncology drug development has been limited by high rates of failure (lack of efficacy) in subsequent phase III testing. This high failure rate may reflect the process by which antineoplastic agents are usually evaluated in phase II trials, i.e., via single-arm studies in which the primary efficacy measure is the proportion of patients who achieve a complete or partial response to the treatment. This design may efficiently eliminate truly ineffective therapy but may not reliably indicate whether subsequent phase III testing is warranted.

METHODS

We describe the design of a randomized phase II clinical trial of sorafenib in combination with erlotinib for the treatment of patients with non-small-cell lung cancer using change in tumor size, measured on a continuous scale, as the primary outcome variable. For the purpose of determining the sample size of the trial, we made assumptions as to the likely magnitude of treatment effect and the variability in tumor size changes based on data from four previous trials using these agents.

RESULTS

The study design includes two different dosage arms and a placebo group with a total sample size of 150 patients and is powered to detect a modest reduction in the mean tumor size burden in the high-dose sorafenib arm compared with a slight increase in the placebo group.

CONCLUSIONS

Clinical trial designs that treat change in tumor size as a continuous variable rather than categorizing the changes are feasible, and by inclusion of a prospective control group they offer advantages over conventional single-arm trials.

Setting the bar in phase II trials: the use of historical data for determining "go/no go" decision for definitive phase III testing

PURPOSE

Phase II trials aim to determine whether a cancer treatment is sufficiently promising to justify phase III study. Whether an agent is declared promising in a phase II trial depends on prespecified "null" and "alternative" rates of an outcome of interest such as tumor response. In some cases, the null must be determined with reference to historical data. We sought to determine the proportion of phase II trials that require historical data to establish the null and to determine how these historical estimates were derived.

EXPERIMENTAL DESIGN

We conducted a systematic review of phase II trials published in the Journal of Clinical Oncology or Cancer in the 3 years to June 2005. Data were extracted following a prespecified protocol.

RESULTS

We retrieved 251 papers, of which 117 were found to be ineligible; 70 of 134 included trials (52%) were defined as requiring historical data for design. Nearly half (32, 46%) of these papers did not cite the source of the historical data used, and just 9 (13%) clearly gave a single historical estimate as the rationale for the null. Trials that failed to cite prior data appropriately were significantly more likely to declare an agent to be active (82% versus 33%; P=0.005). No study incorporated statistical methods to account for either sampling error or possible differences in case mix between the phase II sample and the historical cohort.

CONCLUSIONS

Many phase II trials require historical data to determine null response rates. Simple guidelines may improve design and reporting of such trials.

The relationship between six-month progression-free survival and 12-month overall survival end points for phase II trials in patients with glioblastoma multiforme

Common end points for phase II trials in patients with glioblastoma multiforme (GBM) are six-month progression-free survival (PFS6) and 12-month overall survival (OS12). OS12 can be accurately measured but may be confounded with subsequent therapies upon progression, whereas the converse is true for PFS6. Our goal was to assess the relationship between these end points separately for phase II trials in patients with newly diagnosed GBM and patients with recurrent GBM. Data were pooled from 11 North Central Cancer Treatment Group trials for patients with newly diagnosed GBM (n = 1348). All patients received radiotherapy and pharmaceutical therapy (before, during, or after radiotherapy). Data were pooled from 16 trials that used various pharmaceuticals in treating patients for recurrent GBM (n = 345). All trial regimens were declared nonefficacious by predefined criteria. Overall per-patient concordance was estimated with a kappa statistic. The relationship between OS12 and PFS6 across study arms was assessed by weighted linear regression and Pearson's correlation. Simulation was used to determine the agreement of study outcomes when using PFS6 versus OS12 end points. Cox models with progression status as a time-dependent variable and Kaplan-Meier estimators were used to ascertain the association between progression-free survival status and overall survival. At present, 97% of the patients with newly diagnosed GBM and 95% of those with recurrent GBM have died. The PFS6 and OS12 were 43% and 41%, respectively, for patients with newly diagnosed disease and 9% and 14% for patients with recurrent disease. There was only moderate concordance between the end points on both the patient level and the study level. For the simulation studies, we established phase II efficacy criteria for each end point by using the pooled estimates of OS12 (PFS6) as historical controls. The study decisions made using PFS6 and OS12 were in agreement 88% and 90% of the time for the trials of newly diagnosed and recurrent disease, respectively. Finally, there was a strong association between progression-free survival status and overall survival. PFS6 seems to be a reasonable end point for phase II trials in patients with recurrent glioblastoma.

Comparison of Outcomes of Phase II Studies and Subsequent Randomized Control Studies Using Identical Chemotherapeutic Regimens

Purpose

To determine whether promising results from phase II studies could be reproduced in phase III studies, and to examine which characteristics of phase II studies might be of predictive value for subsequent phase III studies.

Methods

We searched for all phase III studies of chemotherapy in advanced solid malignancies, published in the English language literature from July 1998 to June 2003. Each phase III study was reviewed to identify preceding phase II studies. Phase II and phase III studies included in this analysis must have used identical regimens. Data were extracted from both phase II and phase III studies.

Results

Of 181 phase III studies identified, 43 used therapeutic regimens identical to those in 49 preceding phase II studies. Twelve phase III studies (28%) were “positive.” The vast majority (81%) of phase III studies have lower response rates than preceding phase II studies, with a mean difference of 12.9% among all studies analyzed. None of the phase II study characteristics evaluated significantly predicted for “positive” phase III studies, but the sample size of phase II studies demonstrated a trend toward being predictive (P = .083).

Conclusion

Promising results from phase II studies frequently do not translate into “positive” phase III studies. Response rates in most phase III studies are lower than those in preceding phase II studies.

Prostate cancer clinical trial end points: "RECIST"ing a step backwards

PURPOSE

To relate clinical issues to the clinical manifestations of prostate cancers across disease states using the eligibility and outcome criteria defined by Response Evaluation Criteria in Solid Tumors (RECIST).

EXPERIMENTAL DESIGN

The manifestations of prostate cancer that characterize localized, recurrent, and metastatic disease were considered using the eligibility criteria for trials defined by RECIST. To do so, we analyzed the sites, size, and distribution of lesions in patients enrolled on contemporary Institutional Review Board-approved trials for progressive castrate and noncastrate metastatic disease. Prostate-specific antigen (PSA) levels were also assessed. RECIST-defined outcome measures for tumor regression were then applied to the metastatic patient cohorts, and separately to the states of a rising PSA (noncastrate and castrate) and localized disease.

RESULTS

Only 43.5% of men with castrate metastatic and 16% of noncastrate metastatic disease had measurable target lesions > 2 cm in size. Overall, 84.4% of the target lesions were lymph nodes, of which 67.7% were > or = 2 cm in the long axis. There are no target lesions in patients in the states of a rising PSA and localized disease, making them ineligible for trials under these criteria. PSA-based eligibility and outcomes under RECIST conflict with established reporting standards for the states of a rising PSA and castrate metastatic disease. The clinical manifestations of prostate cancer across multiple disease states are not addressed adequately using the eligibility criteria and outcomes measures defined by RECIST. Important treatment effects are not described.

CONCLUSIONS

Trial eligibility and end points based solely on tumor regression are not applicable to the majority of the clinical manifestations of prostate cancers representing all clinical states. Treatment effects can be described more precisely if eligibility criteria are adapted to the clinical question being addressed and clinical state under study, focusing on the duration of benefit defined biochemically, radiographically, and/or clinically.

Chemotherapy agents and timing of chemotherapy in prostate cancer management

In 2005, it is estimated that more than 30,000 men will die from metastatic hormone-refractory prostate cancer. For decades, no chemotherapeutic agent demonstrated a survival benefit in these patients, although two randomized clinical trials demonstrated a clear palliative benefit using mitoxantrone combined with a corticosteroid. However, beginning in 1999, a series of phase-2 trials were performed using docetaxel, either as a single agent or in combination with estramustine. Preliminary data implied a survival improvement, with median survivals reported to be 14 to 23 months. Prostate-specific antigen levels dropped by more than 50% in 38% to 48% of patients treated with docetaxel. These findings were confirmed in two phase-3 randomized trials in which docetaxel with and without estramustine have demonstrated a survival benefit using chemotherapy in the treatment of hormone-refractory prostate cancer.

A phase II study of concurrent temozolomide and cis-retinoic acid with radiation for adult patients with newly diagnosed supratentorial glioblastoma

PURPOSE

This Phase II study was designed to determine the median survival time of adults with supratentorial glioblastoma treated with a combination of temozolomide (TMZ) and 13-cis-retinoic acid (cRA) given daily with conventional radiation therapy (XRT).

METHODS AND MATERIALS

This was a single arm, open-labeled, Phase II study. Patients were treated with XRT in conjunction with cRA and TMZ. Both drugs were administered starting on Day 1 of XRT, and chemotherapy cycles continued after the completion of XRT to a maximum of 1 year.

RESULTS

Sixty-one patients were enrolled in the study. Time to progression was known for 55 patients and 6 were censored. The estimated 6-month progression-free survival was 38% and the estimated 1-year progression-free survival was 15%. Median time to progression was estimated as 21 weeks. The estimated 1-year survival was 57%. The median survival was 57 weeks.

CONCLUSIONS

The combined therapy was relatively well tolerated, but there was no survival advantage compared with historical studies using XRT either with adjuvant nitrosourea chemotherapy, with TMZ alone, or with the combination of TMZ and thalidomide. Based on this study, cRA does not seem to add a significant synergistic effect to TMZ and XRT.

Considerations when designing a clinical trial of haematopoietic stem cell transplantation for autoimmune disease

The design and conduct of clinical trials of haematopoietic stem cell transplantation (HSCT) for autoimmune diseases requires investigators to address issues unique to this therapeutic approach and patient population. The proper composition of the protocol team is central to success. It is important to recognize that transplant physicians are no longer also the disease experts when transplanting patients with autoimmune diseases, and a close collaborative relationship between these groups early in the design stage must continue through the care of patients on trial to the assessment of toxicity and response. The early involvement of statisticians expert in clinical trial design and patient representatives are also vital to developing the optimal protocol. Each step in design and implementation requires particular consideration of the unique aspects of applying HSCT to autoimmune diseases. Some areas discussed are the role of disease and transplant databases in designing and analysing clinical trials, design options for early-phase trials, maintaining clinical equipoise, eligibility criteria, blinding, outcome measures and statistical analysis, and the composition and role of the data safety and monitoring boards. Although no blueprint for designing and conducting a trial of HSCT for autoimmune diseases can be laid out, the process should take into consideration the issues highlighted herein.

Eligibility and outcomes reporting guidelines for clinical trials for patients in the state of a rising prostate-specific antigen: recommendations from the Prostate-Specific Antigen Working Group

PURPOSE

To define methodology to show clinical benefit for patients in the state of a rising prostate-specific antigen (PSA).

RESULTS

HYPOTHESIS

A clinical states framework was used to address the hypothesis that definitive phase III trials could not be conducted in this patient population.

PATIENT POPULATION

The Group focused on men with systemic (nonlocalized) recurrence and a defined risk of developing clinically detectable metastases. Models to define systemic versus local recurrence, and risk of metastatic progression were discussed.

INTERVENTION

Therapies that have shown favorable effects in more advanced clinical states; meaningful biologic surrogates of activity linked with efficacy in other tumor types; and/or effects on a target or pathway known to contribute to prostate cancer progression in this state can be considered for evaluation.

OUTCOMES

An intervention-specific posttherapy PSA-based outcome definition that would justify further testing should be described at the outset. Reporting: Trial reports should include a table showing the number of patients who achieve a specific PSA-based outcome, the number who remain enrolled onto the trial, and the number who came off study at different time points. The term PSA response should be abandoned.

TRIAL DESIGN

The phases of drug development for this state are optimizing dose and schedule, demonstration of a treatment effect, and clinical benefit. To move a drug forward should require a high bar that includes no rise in PSA in a defined proportion of patients for a specified period of time at a minimum. Agents that do not produce this effect can only be tested in combination. The preferred end point of clinical benefit is prostate cancer-specific survival; the time to development of metastatic disease is an alternative.

CONCLUSION

Methodology to show that an intervention alters the natural history of prostate cancer is described. At each stage of development, only agents with sufficient activity should be moved forward.

The Phase III Trial in the Era of Targeted Therapy: Unraveling the “Go or No Go” Decision

Purpose: To review characteristics of contemporary phase III oncology trials and create an explicit framework to help clinical researchers prioritize novel therapies for phase III testing.

Methods: We searched the MEDLINE and EMBASE databases for all reviews of phase III trials; cataloged all phase III trials in two national clinical trial databases; and reviewed approval criteria of recently approved oncology drugs from public data provided by the US Food and Drug Administration. Industry data not available elsewhere in the medical literature were obtained from a sourcebook published by a large contract research organization.

Results: Phase III oncology trials are the most expensive and time-consuming aspect of the drug development process. The results of these trials continue to exert the greatest influence on the treatment decision of oncologists and remain pivotal to the granting of drug approval. Making optimal decisions about which agents to advance to phase III testing may decrease the overall cost of cancer drug development and limit the number of patients exposed to ineffective drugs. A conceptual decision model for prioritizing novel therapies for phase III testing is presented.

Conclusion: Cancer drug development has become more complex and expensive, whereas overall clinical progress remains slow. The transition from phase II to phase III requires a strategic decision that is based on new considerations. A greater investment in phase I and II drug trials may be required to provide the information necessary for phase III planning.

Is patient travel distance associated with survival on phase II clinical trials in oncology?

BACKGROUND

Prior research has suggested that patients who travel out of their neighborhood for elective care from specialized medical centers may have better outcomes than local patients with the same illnesses who are treated at the same centers. We hypothesized that this phenomenon, often called "referral bias" or "distance bias," may also be evident in curative-intent cancer trials at specialized cancer centers.

METHODS

We evaluated associations between overall survival and progression-free survival and the distance from the patient residence to the treating institution for 110 patients treated on one of four phase II curative-intent chemoradiotherapy protocols for locoregionally advanced squamous cell cancer of the head and neck conducted at the University of Chicago over 7 years.

RESULTS

Using Cox regression that adjusted for standard patient-level disease and demographic factors and neighborhood-level economic factors, we found a positive association between the distance patients traveled from their residence to the treatment center and survival. Patients who lived more than 15 miles from the treating institution had only one-third the hazard of death of those living closer (hazard ratio [HR] = 0.32, 95% confidence interval [CI] = 0.12 to 0.84). Moreover, with every 10 miles that a patient traveled for care, the hazard of death decreased by 3.2% (HR = 0.97, 95% CI = 0.94 to 0.99). Similar results were obtained for progression-free survival.

CONCLUSION

Results of phase II curative-intent clinical trials in oncology that are conducted at specialized cancer centers may be confounded by patient travel distance, which captures prognostic significance beyond cancer stage, performance status, and wealth. More work is needed to determine what unmeasured factors travel distance is mediating.

Prostate carcinoma: defining therapeutic objectives and improving overall outcomes

The development and progression of a prostate carcinoma from prediagnosis to death can be characterized as a series of clinical states. The states are milestones that can be used to assess prognosis, define therapeutic objectives, and assess outcomes. The antitumor effects of hormone therapies and cytotoxic agents in patients with prostate carcinoma are placed in context along with the bidrectional tumor-host interactions that contribute to the growth and resistance of osseous lesions. Identifying the factors that contribute to the growth of the disease at different points in the illness has lead to novel, systemic approaches. Proving the benefit of these approaches requires a series of unique trials with unique endpoints relevant to the clinical state of the patients and the specific therapy under evaluation.

Estimating survival benefit in castrate metastatic prostate cancer: decision making in proceeding to a definitive phase III trial

OBJECTIVES

In designing a Phase II trial, the acceptable clinical activity region for a new therapy is often developed using data from historically treated patients. This region incorrectly ignores the variability of this estimate, because the efficacy of the prior treatment lies somewhere around the estimate. The size of this interval is dependent on the sample size used. This report illustrates the use of a published method that accounts for this uncertainty and aids in the decision to proceed to a definitive trial.

METHODS

A historical data set of low-risk patients with progressive castrate metastatic prostate cancer and a group of similar patients treated in a Phase II chemotherapy trial were used. The 1-year Kaplan-Meier estimate of survival was obtained for both. This approach uses the 75% upper confidence bound of the 1-year survival probability from the historical data set to define the lower limit of acceptable clinical activity. Use of this bound makes the approach more conservative, and hence the decision to proceed to a Phase III trial more difficult.

RESULTS

In the low-risk historical patients, the 1-year Kaplan-Meier estimate of survival was 66.4% (75% upper confidence bound 71.0%). In the Phase II patients, the 1-year Kaplan-Meier estimate of survival was 89.5% (95% lower confidence bound 78.2%).

CONCLUSIONS

A hypothesis test using the 75% upper confidence bound to define the lower limit of acceptable clinical activity demonstrates that the 1-year survival probability on Taxol/estramustine/carboplatin is greater than that of the historical population, and hence should be taken into a definitive trial. The design provides investigators increased confidence in making this decision.

Clinical trial designs for targeted agents

With an increasing number of targeted agents available for testing, clinical trials must be rationally designed based on sound knowledge of the molecular mechanisms linking target and disease, fortified by strong preclinical data demonstrating how this relationship is modified by the targeted agent. Patients and resources are precious and should be expended judiciously on clinical trials that are well planned. Although traditional trial designs and endpoints may not be adequate for developing contemporary targeted drugs, transiting directly from phase I to phase III testing should be avoided except in distinct circumstances. Increased research efforts should be spent on the prospective evaluation and validation of novel biologic endpoints and innovative clinical designs, such that promising targeted agents can be effectively developed to benefit the care of cancer patients.