ARTICLES

Post-therapy Serum Prostate-Specific Antigen Level and Survival in Patients With Androgen-Independent Prostate Cancer

Howard I. Scher, W. M. Kevin Kelly, Zuo-Feng Zhang, Peter Ouyang, Min Sun, Morton Schwartz, Cliff Ding, Weiping Wang, Ivan D. Horak, Alton B. Kremer

Affiliations of authors: H. I. Scher, W. M. K. Kelly, Genitourinary Oncology Service, Division of Solid Tumor Oncology, Department of Medicine, Memorial Sloan-Kettering Cancer Center, and Department of Medicine, Cornell University Medical College, New York, NY; Z.-F. Zhang, M. Sun (Division of Biostatistics, Department of Epidemiology and Biostatistics), M. Schwartz (Department of Laboratory Medicine), Memorial Sloan-Kettering Cancer Center; P. Ouyang, C. Ding, W. Wang, I. D. Horak, A. B. Kremer, Janssen Pharmaceutica, Inc., Titusville, NJ.

Correspondence to: Howard I. Scher, M.D., Memorial Sloan-Kettering Cancer Center, 1275 York Ave., New York, NY 10021.

Present address: Z.-F. Zhang, Department of Epidemiology, School of Public Health and Johnson Comprehensive Cancer Center, University of California at Los Angeles, CA.

Present address:M. Sun, Department of Epidemiology, School of Public Health and Johnson Comprehensive Cancer Center, University of California at Los Angeles, CA.


    ABSTRACT
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
BACKGROUND: With an hypothesis that post-chemotherapy changes in serum prostate-specific antigen (PSA) levels might serve as a surrogate marker for assessing prostate cancer outcome (i.e., survival), we studied the relationship between pretherapy and post-therapy prognostic factors and survival in patients with androgen-independent prostate cancer. METHODS: A prognostic model for survival based on pretherapy and post-therapy parameters was developed from the clinical data on 254 patients with androgen-independent prostate cancer treated with 11 different protocol therapies at Memorial Sloan-Kettering Cancer Center. The model was validated by use of an independent dataset of 541 patients enrolled in two randomized phase III trials. RESULTS: In multivariate analysis, a post-therapy decline in PSA levels of 50% achieved in 12 weeks was a statistically significant factor associated with survival (two-sided P = .0012). A similar outcome was obtained with the use of an 8-week time frame. Elevated pretherapy level of serum lactate dehydrogenase (two-sided P = .0001), lower pretherapy level of hemoglobin (P = .0001), and younger age (two-sided P = .0430) had a statistically significant negative impact on outcome. Median survival times were 23, 17, and 9 months for low-, intermediate-, and high-risk groups of patients defined by the prognostic model, respectively. CONCLUSION: This study confirms the prognostic value of a post-therapy decline in PSA of 50% or greater from baseline in relation to survival in patients with androgen-independent prostate cancer treated with a variety of therapies. Two consecutive determinations at 4-week intervals can be used as an end point for efficacy in phase II trials of therapies in this disease.



    INTRODUCTION
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Identifying new therapeutic approaches for metastatic prostate cancer is limited by the fact that most metastases are to bone, where the growth or regression of a tumor is difficult to quantitate in a reproducible way. Prostate-specific antigen (PSA) is a single-chain glycoprotein produced by the epithelial cells of the prostate that functions as a kallikrein-like serine protease (1). It has been used for early detection and staging of tumors and for monitoring patients with prostate cancer of different stages who receive a variety of treatments (2). Because serum levels of PSA can be measured reliably and reproducibly and rising values precede worsening of a bone scan or the development of cancer-related symptoms, we hypothesized that post-therapy changes in PSA levels might be used as an outcome measure for screening phase II trials in patients with androgen-independent disease. The approach obviates the need to restrict entry on trials to patients with measurable disease, and, if the association between a defined post-therapy change in level could be validated with a clinically meaningful end point such as survival, it would allow more approaches to be tested in a shorter time frame (3).

Our original report (4) showing an association between a post-therapy decline in PSA levels and survival was unique in that it included multivariate techniques that were validated by the use of an independent dataset. Since then, numerous reports (5-14) have appeared with seemingly conflicting results. Contributing to the conflicts are inconsistencies in the "criteria" used to classify a patient into a category of "response" (presumed to be of benefit to the patient) or "no response" (no benefit). This situation was shown when we categorized the same cohort of patients by use of different criteria of post-therapy PSA changes; the proportion of "responders" ranged from 5% to 45% (15). The statistical techniques applied also differed, but most noteworthy is that few analyses used multivariate techniques and an independent dataset for validation. It is also likely that a PSA-based outcome measure may be appropriate for some, but not for other, classes of drug and that different post-therapy PSA change definitions would be needed for drugs that act by different mechanisms.

The more important consideration is that it was not our intent that a single "categorical" definition of post-therapy PSA change (i.e., no change, >=50% decline, or >=80% decline from baseline) be a surrogate for "response." Rather, we intended to provide a reproducible trial end point that could be used to decide whether an approach was of sufficient benefit to justify continued clinical development and, if so, for sample size considerations in the design of prospective confirmatory phase II and phase III trials.

In this study, we explored associations between pretherapy variables including the rate of rise in PSA levels prior to treatment, different definitions of a post-therapy PSA decline, and survival in a larger cohort of patients treated at the Memorial Sloan-Kettering Cancer Center (MSKCC) with the aim of standardizing reporting of outcomes. A multivariate model to predict survival was then derived. We tested the model and validated it on an independent dataset of patients enrolled in two randomized phase III trials that compared liarozole, a drug that inhibits retinoic acid metabolism (16), with prednisone (the USA 22 trial) and liarozole with cyproterone acetate, a type I mixed progestational anti-androgen (the INT 5 trial).


    PATIENTS AND METHODS
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
MSKCC Patient Population

Two hundred fifty-four patients with androgen-independent prostate cancer treated on 11 consecutive studies from 1987 through 1994 at MSKCC were included. All had documented progressive disease despite castrate levels of testosterone defined as 1) a rising PSA level of 50% or greater from baseline on three successive occasions, 2) new metastatic lesions on bone scan, or 3) a 25% or greater increase in a bidimensionally measurable tumor mass. Although the individual treatment programs differed with respect to the requirement for measurable or evaluable disease, the pretreatment evaluations were similar. A complete medical history was obtained from all patients. All patients also underwent a physical examination. Laboratory studies included an automated blood cell and platelet count, 12 channel screening profiles (alkaline phosphatase, lactate dehydrogenase, aspartate transglutaminase, blood urea nitrogen, creatinine, calcium, phosphorus, glucose, uric acid, total protein, albumin, and total bilirubin), measurement of serum acid phosphatase, and PSA measurement. Imaging studies included an abdominal and pelvic computed tomography or magnetic resonance imaging and bone scan. Patients were treated according to the individual program on which they were enrolled.

In general, therapeutic outcomes were assessed at 8-week intervals unless clinically indicated. Post-therapy PSA determinations were performed at a minimum of every 4 weeks. All patients were followed until death or censored at last follow-up. Case patients who were enrolled in more than one study were evaluated only on their first treatment.

All clinical trial data were obtained in full compliance with MSKCC institutional review board requirements for studies involving human subjects. All patients enrolled in MSKCC-approved research investigations provide written informed consent before being enrolled in an MSKCC clinical trial.

Analysis of Prognostic Factors

Variables explored included performance status (Karnofsky) at baseline, sites of disease, baseline measurements, pretherapy PSA incline slope, and post-therapy PSA decline (>=50% from baseline). Demographics included age as a dichotomous (>70 years old versus <=70 years old) or continuous variable and histologic grade of the tumor at the time of initial diagnosis. Baseline measurements included serum PSA levels (ng/mL), serum acid phosphatase levels (U/L), serum alkaline phosphatase levels (U/L), serum lactate dehydrogenase levels (U/L), serum hemoglobin levels (g/dL), serum creatinine levels (mg/dL), serum albumin levels (g/dL), serum glutamic-oxalacetic transaminase levels (U/L), and serum testosterone levels (ng/dL). On the basis of our previous analysis showing no association, prior radiation therapy, prior surgery, type of primary hormone therapy, and duration of response to primary therapy were not considered.

The variable pretherapy PSA rate of rise was designed to estimate rates of progression prior to protocol treatment. It was calculated for an individual patient by fitting a regression line to a minimum of three or more PSA determinations (if available) obtained prior to treatment, if there was no change in treatment during the interval over which the PSA measurements were obtained. The slope of the fitted line was used as the independent variable, and survival was used as the dependent variable in a regression model.

After treatment, PSA values were plotted, and patients were categorized into one of two mutually exclusive categories based on whether or not they achieved a post-therapy PSA decline (>=50%) by use of three different methods of assignment. The first method of assignment required two consecutive PSA declines, each less than 50% of the baseline value, achieved by, but not necessarily maintained past, the landmark period of 8 or 12 weeks. The second method required two consecutive PSA declines, each less than 50% of the baseline value, which was maintained at or past the landmark period of 8 or 12 weeks. The third method required two consecutive PSA declines, each less than 50% of the baseline value, which was maintained for a minimum of 8 weeks. This condition had to be satisfied by week 12 (the landmark period). These landmarks were considered because the intervals correspond to the points at which "response" assessments are typically performed in phase II trials.

Statistical Analysis

The survival distributions of the pretherapy parameters analyzed as categorical variables were compared by the logrank test (17) with a level of statistical significance <=.05. Most cut points were based on the upper limits of normal for the parameter. To avoid subjectivity in selecting a break point, we also evaluated continuous variables by the Wald test using the proportional hazards model. Furthermore, to reduce the potential for bias in the evaluation of patients who met the criteria for PSA decline versus those who did not, 8- and 12-week landmarks were investigated (vide supra) (18). Patients whose survival was shorter than the landmark point were excluded from the analysis. "PSA response" was evaluated according to the above-mentioned methods of assignment by use of a computer program. Patients were then followed forward in time to ascertain whether survival from the landmark depended on whether or not the defined post-therapy change in PSA levels for that patient met the criteria established for the 8- and 12-week time periods.

Survival distributions were estimated by the Kaplan-Meier method (19), and median survival times were reported from the start of therapy. For these calculations, the LIFETEST procedure in Statistical Analysis System was used (20). All patients who died were considered treatment failures, whereas patients alive at last follow-up were classified as censored in the survival analysis. Proportional hazards analysis was used to obtain maximum likelihood estimates of relative risks and their 95% confidence intervals (CIs) in univariate and multivariate analyses (21,22). All parameters significant at the .05 level in univariate analysis were evaluated in the multiple proportional hazard model. Stepwise, backward and forward iterative processes were employed to obtain the final prognostic model. All reported P values are two-sided.

Validation of MSKCC Model With the Use of an Independent Dataset

To validate the final model derived from the MSKCC population, we used a combined independent dataset of patients enrolled in two randomized phase III trials that compared liarozole (16) and prednisone (USA 22 trial) and liarozole and cyproterone acetate (INT 5 trial). In these trials, PSA measurements were obtained at 4-week intervals.

The validation process involved the calculation of a risk score (R) for each patient in the validation dataset using the final model obtained from the MSKCC data by use of the following equation:


where the coefficients (ß) are estimated from the proportional hazards model obtained from the MSKCC data and Xnrepresents the significant prognostic factor(s) in the model. Patients were then divided on the basis of the R score into three equal groups. Within each of the three risk groups, Kaplan-Meier estimates of survival were computed. These estimates were then compared with the MSKCC model-based estimates of survival.


    RESULTS
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
Patients Treated at MSKCC

There were a total of 254 patients followed for a median of 39 months (range, 1-58.2 months); of these patients, 200 (79%) died of prostate cancer (Tables 1Go and 2).Go The median age of the patients was 67 years. Prior therapy included one hormonal manipulation in 49.6% and two in 35.8%, while 12.2% had three or more hormonal interventions. Protocol therapy included suramin in 39.4%, rhenium-186 hydroxyethylidene diphosphonate in 28.0%, Casodex (high dose) in 16.1%, 13-cis-retinoic acid and interferon alfa in 6.3%, edatrexate in 5.5%, and all-trans-retinoic acid in 4.7% of cases. The baseline biochemical parameters reflected a range of disease severity that was also shown by the median baseline PSA level of 96 ng/mL (range, 0-8450 ng/mL). The median survival of the population was 12.9 months (95% CI = 11.3-15.8 months), of whom 89% survived 12 weeks or more, and 13% showed a 50% or greater decline in PSA levels from baseline following the criteria defined for the 12-week landmark using the first method of assignment (vide supra).


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Table 1. Patient characteristics: Memorial Sloan-Kettering Cancer Center

 

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Table 2. Treatment outcomes

 
Univariate Analysis

The results of the univariate survival analysis are presented in Table 3.Go Older age was associated with a longer survival whether analyzed as a dichotomous variable (>70 years of age versus <=70 years of age; median survival of 15.4 months versus 11.3 months, respectively) but was statistically significant only when analyzed as a continuous variable in the proportional hazards model (P = .045).


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Table 3. Results of univariate analysis of baseline variables for the Memorial Sloan-Kettering Cancer Center cohort

 
Pretherapy parameters (excluding PSA). Several pretherapy biochemical parameters were significantly associated with survival. In particular, patients with a high hemoglobin level and normal albumin, alkaline phosphatase, lactate dehydrogenase, and acid phosphatase levels had a longer survival than those with abnormal baseline measures. The presence of bone metastases, documented in 234 (92.1%) patients, was associated with an inferior survival relative to that of the 20 patients with disease limited to lymph node sites and no bone disease (logrank test: P = .02), but no difference in survival was observed in patients who had bone and soft tissue disease compared with that in patients who had bone-only disease. Within the ranges studied, baseline creatinine and baseline testosterone levels were not statistically significantly associated with mortality. A serum glutamic-oxalacetic transaminase level of 50 U/L or more, however, was of borderline statistical significance (P = .06).

Pretherapy PSA rate of rise. A minimum of three (median, four) consecutive pretherapy PSA measurements was available for 158 patients to calculate a pretherapy slope by use of a fitted regression line. The calculated slope was then used in a regression model to explore associations with survival. No association was observed (P = .46).

Baseline PSA. When evaluated as a continuous variable in the proportional hazards model, baseline PSA levels were predictive of survival (P = .0011). As a discrete variable, patients with a baseline PSA level of greater than 100 ng/mL had inferior outcomes relative to those with a baseline PSA level of 100 ng/mL or below; the median survivals were 10.6 months versus 17.1 months, respectively (P = .0006).

Post-therapy PSA decline. The median survival for 26 patients who met the criteria for a 50% or greater decline in PSA levels from baseline at 8 weeks (11% of the population) was 23.6 months versus 12.3 months for those who did not show a post-therapy PSA decline (logrank test: P = .0002). With the use of a 12-week landmark, the respective median survivals were 25.3 months versus 13 months (logrank test: P = .0001). Similar results were obtained with the use of the second and third methods of assignment for a post-therapy decline in PSA levels.

Multivariate Analysis

All factors that were statistically significant at the .05 level in the univariate analysis were included in the multivariate proportional hazards model using stepwise, forward and backward processes to obtain the final model. The results, presented in Table 4,Go were similar with each modeling technique. As shown, a 50% or greater decline in PSA levels within 12 weeks was a statistically significant predictor of survival (risk ratio = 2.31; 95% CI = 1.39-3.81). An increased baseline serum lactate dehydrogenase level was a negative predictor, whereas a higher baseline serum hemoglobin level and older age were associated with improved outcomes and were more predictive than post-therapy PSA decline. Once these factors were included, no other factors retained statistical significance.


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Table 4. Multivariate model for survival of patients treated at the Memorial Sloan-Kettering Cancer Center*

 
Independent Dataset

Univariate analysis of PSA decline. We employed a combined independent dataset of 541 patients from two randomized phase III trials to validate the final model from MSKCC data. Two patients were excluded because of missing survival data. The baseline demographics for the populations enrolled on each of two randomized comparisons as well as for the entire population are included in Table 5Go and, with the exception of age, were similar to those for the MSKCC cohort. Four hundred three patients (75%) died of disease during the study period with a median survival of 11.4 months compared with the 12.9-month median survival for the MSKCC population (see Table 2Go). The median age for this cohort of patients was 72 years (range, 46-94 years), which was older than that for the MSKCC cohort (median age, 67 years; range, 45-86 years) (see Table 1Go).


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Table 5. Patient characteristics: USA 22 and INT 5*

 
The same criteria for PSA decline and the same 8-week and 12-week landmarks were applied to the independent dataset in which PSA determinations were obtained at 4-week intervals. Four hundred twenty-eight patients (79%) survived 8 weeks or longer, and 409 patients (76%) survived 12 weeks or longer (see Table 2Go). There were 53 patients (10%) with a 50% or greater post-therapy decline in PSA levels from baseline at 8 weeks and 64 patients (12%) who met the same criteria at 12 weeks (see Table 2Go). These proportions were similar to those observed for patients treated at MSKCC (10% within 8 weeks and 13% within 12 weeks, respectively [Table 2Go]). Patients with a 50% or greater reduction in two consecutive PSA measures within 8 weeks had a statistically significantly longer survival (20.4 months) than those without a PSA reduction (12.9 months; logrank test: P = .0208). For a landmark of 12 weeks, the median survival was 20.8 months for those with a reduction in the PSA levels and 13.7 months for those without a decline in PSA levels (logrank test: P = .0038).

Validation of PSA decline with the use of the independent dataset. The four major predictors (i.e., >=50% decline in PSA values at 12 weeks, baseline lactate dehydrogenase level, baseline hemoglobin level, and age) identified in the multivariate model developed from the MSKCC population were used to calculate the risk of death for each patient in the independent dataset. The final model was as follows:

1) Rj = 0.834864 x 50% PSA decline within 12 weeks + 0.002504 x baseline lactate dehydrogenase - 0.193959 x baseline hemoglobin - 0.022341 x age.

By use of this model, an 80-year-old man who had a pretreatment lactate dehydrogenase level of 230 U/L and a hemoglobin level of 13 g/dL and who did not have a post-therapy PSA decline (coded as 1) would have the following risk score:




2) The survival function Sj for each patient in the validation dataset was then estimated, and the entire population was divided into three equal groups according to risk score. Patients with a risk score less than -2.856 were considered at low risk; those with risk scores between -2.856 and -2.391 were considered at intermediate risk, and those with risk scores above -2.391 were considered at high risk. The median survival times were 23, 17, and 9 months for the low-, intermediate-, and high-risk groups, respectively. The average of the survival function for each event point for each risk group was then calculated. Fig. 1Go shows the predicted survival function for three risk groups classified by use of the MSKCC-derived model plotted against the observed Kaplan-Meier curve for each risk group. The predicted and observed 1-, 2-, and 3-year survival rates are shown in Table 6.Go Similar survival rates were identified at 1 year and at 2 years. In year 3, some discrepancy was observed and may reflect the small number of patients alive at that point in time.



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Fig. 1. Kaplan-Meier estimates of the observed versus predicted survival for the three risk groups (see text for details). Patients from the independent dataset were assigned risk scores based on the multivariate model derived from the Memorial Sloan-Kettering Cancer Center-treated patients (Table 4Go). The derived risk score was used to assign patients into one of three prognostic groups—low-risk, intermediate (Int)-risk, or high-risk group. The observed versus predicted survival along with 95% confidence intervals at 12 and 24 months were estimated with the use of the method of Kaplan and Meier. A close correspondence between the observed and predicted survival distributions was observed.

 

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Table 6. Observed and predicted survivals in the independent dataset*

 

    DISCUSSION
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 
A change in a tumor marker after treatment is of value to a patient if it provides clinically meaningful information on the status of the disease or if it can be used to guide therapy (23). The present study confirms the prognostic significance of a post-therapy decline in PSA levels of 50% or greater from baseline (4) in relation to survival by use of a multivariate model developed from patients treated on a single-arm phase II trial and validated on two independent cohorts of patients with androgen-independent disease enrolled in two randomized clinical trials. The predicted survival function based on the MSKCC model closely approximated the survival curves of the independent dataset. Only one decision rule for a PSA response (a >=50% decline from baseline) was explored. Although the finding of a 50% or greater decline in PSA does not exclude other post-therapy decision rules (such as an 80% or greater decline or no change in PSA level from baseline) as valid, it does suggest that agents producing this degree of decline for a defined duration in a predetermined proportion of patients should continue in clinical development. The conditions of surrogacy, as defined by Prentice et al. (24), cannot be met because they require the demonstration of a treatment effect in a randomized comparison that is eliminated by the inclusion of the proposed intermediate marker or surrogate in a prognostic model.

The association between a 50% or greater decline in PSA levels and survival was observed by use of the MSKCC dataset irrespective of whether an 8- or 12-week landmark was considered and with two or three values meeting the defined criteria of decline. The post-therapy decline definition corresponded to two measurements at 4-week intervals for the independent dataset. The pretherapy rise in PSA levels, which was used as an index of disease aggressiveness, did not have an impact on outcomes in this dataset. Baseline performance status did not add to the association when hemoglobin level, lactate dehydrogenase level, and age were considered. The lack of an association in this model does not exclude the importance of this parameter in relation to other factors in other models.

A post-therapy decline in PSA levels of 50% or greater was not the only factor having an impact on outcome. Other factors of statistical significance were the baseline serum lactate dehydrogenase level, baseline hemoglobin level, and age. When these factors were considered, performance status at baseline did not add predictive value, which may be a function of the small number of patients with a poor performance status at baseline enrolled in these trials (14). Similarly, although an improved outcome was observed for patients with disease limited to soft tissue only versus soft tissue and bone or bone alone, these parameters did not enter the final model.

Not all groups have observed the association between a post-therapy decline in PSA levels and survival (11,25,26). Two of the trials included patients treated with suramin (11,26), an agent known to inhibit PSA release from cells (27), resulting in an appropriate note of caution regarding the use of this end point in clinical trials (28). A similar lack of association between a decline in PSA levels and survival was observed in a large randomized trial of patients with hormone-naive disease addressing the question of whether the addition of flutamide to orchiectomy results in an improved outcome relative to orchiectomy alone (29). It is known, however, that androgens function through an androgen response element on the PSA promoter to increase expression of the gene. Ablating androgens decreases expression (30-33). Does the finding of an effect of a drug or a particular type of treatment mean that a post-therapy decline in PSA levels cannot be used as an end point for phase II screening trials in all stages of the disease? No, but it suggests that it may not be appropriate for clinical trials of hormonal treatments in patients who are hormone naive or who have noncastrate levels of testosterone. What about suramin and hydrocortisone in androgen-independent disease? In one trial showing no association, the categorization of patients as responders or nonresponders was based on a single PSA measurement at 4 weeks relative to baseline (11). This is the time frame in which transient declines in PSA levels that are not durable can be observed (34). In the present study, the association was observed, although 40% of the population received suramin. A difference was that patients in our study were not categorized until week 8 or week 12, a more typical time for outcome assessments, which may have reduced the chance of classifying patients who did not show sustained declines into a "response" or "benefit" category. An additional difference was that we required that the decline be documented on more than one occasion, which, on the basis of the validation set in the current trial, translated into two determinations beginning at week 4 or week 8 and repeated 4 weeks later.

The issue of the androgen regulation of PSA is less applicable to tumors that are proliferating despite castrate levels of testosterone. It has long been recognized that, based on similar estimates of tumor burden, levels of PSA are quantitatively lower in patients with androgen-independent as opposed to androgen-dependent disease (35). Castration results in a lower "set point" at baseline, similar to that described for patients with benign prostatic hyperplasia enrolled in trials in which the 5{alpha}-reductase inhibitor finasteride was used (36). Androgens are not the only agents that can affect PSA gene expression, synthesis, or release into the circulation without affecting cell proliferation or cell kill. Other agents include phorbol esters (37), differentiating agents such as the retinoids (38,39), phenylbutyrate and phenylacetate (40,41), the Chinese herbal preparation PC-SPES (42), and the calcium channel influx inhibitor carboxyamidatriazole (43). Most can be anticipated by first evaluating the effect of the compound on PSA in vitro and then inspecting the patterns of change after treatment in phase I investigations (34). In general, following treatment with a cytotoxic drug, durable declines in PSA levels are associated with other measures of benefit, including regressions in measurable disease, improvements in radionuclide bone scans, and a decrease in cancer-related pain. In contrast, successful differentiation of a cell may result in an increase in PSA levels followed by a decline when overall cell mass is reduced (34). In trials of this class of compounds, a different post-therapy PSA decision rule will be required for screening phase II investigations.

The present study explored only a 50% or greater decline from baseline as the outcome measure, in part because of the level of efficacy of the agents explored. Other decision rules, i.e., a 75% or greater or an 80% or greater decline, have been proposed as more "valid." Lost in these discussions is the fact that defining an "optimal" post-therapy pattern of change does not address the issue of how much of the observed association between a given degree of change in PSA levels and survival can be explained on the basis of the post-therapy change in PSA levels alone. Until this issue has been addressed, the critical question is whether satisfying a proposed decision rule, be it a given degree of decline, no change, or slowing of the rate of rise, in a predetermined proportion of patients in a phase II trial justifies the continued development of a compound or combination of agents. It is our view that it does, with the recognition that treatment is rarely stopped when the PSA level is declining. Nevertheless, because there are other post-therapy changes in PSA that may prove to have prognostic significance, we suggest that the expression "PSA response" not be used and that investigators define the decision rule utilized in their respective trials. Avoiding the expression "PSA response" will allow all groups to place their results in the context of others as we await prospective validation studies.

The observation that patients with soft tissue and osseous disease had outcomes similar to those of patients with osseous disease alone suggests that phase II clinical trials need not be restricted to patients with measurable disease. At this stage, however, it remains essential that associations between changes in PSA levels with other measures of outcome, such as changes in the physical examination, radiographs, scans, and symptoms, continue to be assessed. It is further recommended that PSA measurements be performed in the same laboratory and that changes be reported on the basis of the percent decline, the number of times this decline is documented, the interval between measurements, and the duration of time the decline is maintained so that results can be analyzed and interpreted in a consistent manner (34). Ultimately, any "criteria" proposed will need to be prospectively validated in phase III trials (23).


    NOTES
 
H. I. Scher in 1996 and 1997 was a paid consultant for Janssen Pharmaceutica, Inc., and, although the consulting work was terminated, he collaborated with Janssen Pharmaceutica, Inc., on the analysis of the data performed in this study, which was independent of the clinical trials sponsored by Janssen Pharmaceutica, Inc. A. B. Kremer is an employee of Janssen Pharmaceutica, Inc. P. Ouyang, W. Wang, and I. D. Horak are employees of the Janssen Research Foundation, which sponsored the liarozole clinical trials.

Supported by Public Health Service grants CA05826 and CA09207 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services; by CaPCURE; by The Tarnapol Foundation; and by the PepsiCo Foundation.


    REFERENCES
 Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Discussion
 References
 

1 Lilja H. A kallikrein-like serine protease in prostatic fluid cleaves the predominant seminal vesicle protein. J Clin Invest 1985;76:1899-903.[Medline]

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Manuscript received February 12, 1998; revised November 16, 1998; accepted November 27, 1998.


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