Sigel K

Background: Oncologists evaluating tumor size after anticancer therapy in patients observe the net result of 2 phenomena: regression of the sensitive tumor fraction and growth of the resistant fraction occurring simultaneously at rates that are constant. We have employed simple mathematical models with single and multi-institutional data sets to estimate 2 exponential rate constants: one for tumor regression or decay (d) and one for tumor growth (g). We have (1) established that g correlates with overall survival; (2) demonstrated changes in g after treatment is discontinued; and (3) benchmarked effectiveness in small 20 to 30 patient cohorts to reference data sets from randomized phase 3 trials. Our approach is novel and not another modification of PSA doubling time or velocity, which cannot estimate regression or growth rates while a patient receives therapy. It allows us to determine treatment efficacy regardless of the interval between measurements, which often varies in clinical practice. Our ultimate goals are to establish a reliable method to assess efficacy, provide support for clinical decisions and increase access to clinical trials.

Methods: For the current study we applied our methodology to assess treatment effectiveness among Veterans with prostate cancer (PC) at the J.J. Peters VAMC. To do this we captured serial PSA values and dates when treatment with abiraterone and enzalutamide were started and stopped.

Results: Our initial analysis has examined data from twenty Veterans with PC. The majority had received abiraterone first followed by enzalutamide. With both therapies we found excellent fit of data. Despite wide variations in assessment intervals, g could be calculated in all patients. The median g on abiraterone (0.00086) was fourfold slower than on enzalutamide (0.0035), a statistically significant difference (P = .022). In individual patients we demonstrated comparable g values on abiraterone and enzalutamide in some, but increased g in half the patients when switched to enzalutamide.

Conclusions: Using observational data and a novel method to assess efficacy, we have compared the effectiveness of PC therapies administered to Veterans. Our VAMC data will be benchmarked against publicly available data from registration trials.

Background: Oncologists evaluating tumor size after anticancer therapy in patients observe the net result of 2 phenomena: regression of the sensitive tumor fraction and growth of the resistant fraction occurring simultaneously at rates that are constant. We have employed simple mathematical models with single and multi-institutional data sets to estimate 2 exponential rate constants: one for tumor regression or decay (d) and one for tumor growth (g). We have (1) established that g correlates with overall survival; (2) demonstrated changes in g after treatment is discontinued; and (3) benchmarked effectiveness in small 20 to 30 patient cohorts to reference data sets from randomized phase 3 trials. Our approach is novel and not another modification of PSA doubling time or velocity, which cannot estimate regression or growth rates while a patient receives therapy. It allows us to determine treatment efficacy regardless of the interval between measurements, which often varies in clinical practice. Our ultimate goals are to establish a reliable method to assess efficacy, provide support for clinical decisions and increase access to clinical trials.

Methods: For the current study we applied our methodology to assess treatment effectiveness among Veterans with prostate cancer (PC) at the J.J. Peters VAMC. To do this we captured serial PSA values and dates when treatment with abiraterone and enzalutamide were started and stopped.

Results: Our initial analysis has examined data from twenty Veterans with PC. The majority had received abiraterone first followed by enzalutamide. With both therapies we found excellent fit of data. Despite wide variations in assessment intervals, g could be calculated in all patients. The median g on abiraterone (0.00086) was fourfold slower than on enzalutamide (0.0035), a statistically significant difference (P = .022). In individual patients we demonstrated comparable g values on abiraterone and enzalutamide in some, but increased g in half the patients when switched to enzalutamide.

Conclusions: Using observational data and a novel method to assess efficacy, we have compared the effectiveness of PC therapies administered to Veterans. Our VAMC data will be benchmarked against publicly available data from registration trials.

Background: Oncologists evaluating tumor size after anticancer therapy in patients observe the net result of 2 phenomena: regression of the sensitive tumor fraction and growth of the resistant fraction occurring simultaneously at rates that are constant. We have employed simple mathematical models with single and multi-institutional data sets to estimate 2 exponential rate constants: one for tumor regression or decay (d) and one for tumor growth (g). We have (1) established that g correlates with overall survival; (2) demonstrated changes in g after treatment is discontinued; and (3) benchmarked effectiveness in small 20 to 30 patient cohorts to reference data sets from randomized phase 3 trials. Our approach is novel and not another modification of PSA doubling time or velocity, which cannot estimate regression or growth rates while a patient receives therapy. It allows us to determine treatment efficacy regardless of the interval between measurements, which often varies in clinical practice. Our ultimate goals are to establish a reliable method to assess efficacy, provide support for clinical decisions and increase access to clinical trials.

Methods: For the current study we applied our methodology to assess treatment effectiveness among Veterans with prostate cancer (PC) at the J.J. Peters VAMC. To do this we captured serial PSA values and dates when treatment with abiraterone and enzalutamide were started and stopped.

Results: Our initial analysis has examined data from twenty Veterans with PC. The majority had received abiraterone first followed by enzalutamide. With both therapies we found excellent fit of data. Despite wide variations in assessment intervals, g could be calculated in all patients. The median g on abiraterone (0.00086) was fourfold slower than on enzalutamide (0.0035), a statistically significant difference (P = .022). In individual patients we demonstrated comparable g values on abiraterone and enzalutamide in some, but increased g in half the patients when switched to enzalutamide.

Conclusions: Using observational data and a novel method to assess efficacy, we have compared the effectiveness of PC therapies administered to Veterans. Our VAMC data will be benchmarked against publicly available data from registration trials.