771P - Analysis of overall survival (OS) for patients (pts) with different prognostic risk factors treated with cabazitaxel and prednisone (Cbz + P) after...

Date 27 September 2014
Event ESMO 2014
Session Poster Display session
Topics Anti-Cancer Agents & Biologic Therapy
Prostate Cancer
Presenter Kim Chi
Citation Annals of Oncology (2014) 25 (suppl_4): iv255-iv279. 10.1093/annonc/mdu336
Authors K.N. Chi1, J.S. De Bono2, A. Bahl3, S. Oudard4, B. Tombal5, M. Ozguroglu6, S. Hansen7, I. Kocak8, G. Gravis9, L. Shen10, Z. Su11, O. Sartor12
  • 1Oncology, British Columbia Cancer Agency, V5Z 4E6 - Vancouver/CA
  • 2Drug Development Unit, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, SM2 5PT - Sutton/GB
  • 3Bristol Haematology And Oncology Centre, University Hospitals Bristol NHS Foundation Trust, Bristol/GB
  • 4Medical Oncology, Hôpital Européen Georges Pompidou, René Descartes University, 75015 - Paris/FR
  • 5Division Of Urology, Cliniques Universitaires Saint-Luc, 1200 - Brussels/BE
  • 6Department Of Medical Oncology, Cerrahpasa Medical Faculty, Istanbul University, 34098 - Istanbul/TR
  • 7Department Of Oncology, Odense University Hospital, 2000 - Odense/DK
  • 8Department Of Complex Oncology Care, Masarykuv Onkologicky Ustav, 656 53 - Brno/CZ
  • 9Medical Oncology, Institut Paoli Calmette, Hôpital de Jour, 13273 - Marseille/FR
  • 10Research And Development, Sanofi, 08807 - Bridgewater/US
  • 11Oncology, Sanofi Oncology, Cambridge/US
  • 12Department Of Medicine: Section Of Hematology & Medical Oncology And Department Of Urology, Tulane University, 70112 - New Orleans/US

Abstract

Aim

TROPIC (NCT00417079) showed improved OS for Cbz + P vs. mitoxantrone (Mtx) + P in pts with metastatic castration-resistant prostate cancer (mCRPC). Cbz + P had a manageable safety profile similar to other chemotherapies (ctx). A novel prognostic model using TROPIC and SPARC trial data was developed to predict and validate OS in men with mCRPC progressing during/after D and scheduled to receive second-line ctx. The model identified 9 factors: presence of pain, measurable disease or visceral disease; ECOG PS; time since last D; time from first hormone therapy; haemoglobin (Hb); prostate-specific antigen (PSA); and alkaline phosphatase (ALP). The aim of this study was to explore the activity of Cbz + P in pts with different numbers of prognostic factors.

Methods

We classified pts' prognoses based on number of poor prognostic factors present (presence of pain, measurable disease or visceral disease; ECOG PS [2/0,1]; time since last D [≤6/ > 6 months]; time from first hormone therapy [≤3.6/ > 3.6 yrs]; Hb [<120/ ≥ 120 g/L]; PSA [≥135/ < 135 ng/mL]; ALP [>133/ ≤ 133 IU/L]). OS was compared between Cbz + P and Mtx + P in different groups defined by increasing numbers of poor prognostic factors.

Results

597 pts were included (158 pts had missing prognostic factor data). Using various definitions based on number of poor prognostic factors, pts grouped as good, intermediate or poor risk consistently demonstrated a significant difference in OS (p < 0.0001). Furthermore, Cbz + P consistently improved OS vs Mtx + P independent of increasing numbers of poor prognostic factors.

Conclusions

Increasing numbers of poor prognostic factors were associated with worse OS. Cbz + P improved OS vs Mtx +P regardless of the number of poor prognostic factors present.

No. of factors Patients, n Estimated median OS (95% CI), months Cbz vs Mtx
Cbz Mtx Hazard ratio (95% CI) p-value
0–3 228 28.5 (24.9, –) 23.7 (18.7, –) 0.57 (0.40, 0.83) 0.0032
≥4 369 12.1 (10.5, 13.8) 9.7 (8.4, 11.2) 0.72 (0.57, 0.90) 0.0043
≥5 229 11.0 (9.2, 12.6) 8.3 (7.0, 10.0) 0.64 (0.48, 0.85) 0.0022
≥6 129 9.2 (6.0, 11.6) 7.4 (6.9, 8.6) 0.69 (0.48, 1.01) 0.0532
≥7 62 8.8 (5.6, 11.0) 6.3 (3.9, 7.4) 0.44 (0.25, 0.76) 0.0033

Disclosure

K.N. Chi: has held a compensated consultant/advisory role for Sanofi; J.S. de Bono: has received research funding from the Institute of Cancer Research; A. Bahl: has held a consultant/advisory role and received honoraria and research funding from Sanofi; S. Oudard: has held a consultant/advisory role and received honoraria and research funding from Sanofi; B. Tombal: has held a consultant/advisory role and received honoraria from Sanofi; M. Özgüroğlu: participated in advisory boards for Sanofi; S. Hansen: has held a compensated consultant/advisory role for Sanofi; L. Shen: is an employee (Biostatistics Director) of Sanofi and holds Sanofi stock; Z. Su: is an employee (Medical Director) of Sanofi and holds Sanofi stock; O. Sartor: has held a compensated consultant/advisory role for Sanofi. All other authors have declared no conflicts of interest.