INTRODUCTION: Paclitaxel plus cisplatin is considered to be the standard first-line therapy for advanced ovarian cancer. Previous to this study, economic data on this combination resulted from randomised clinical trials (RCTs). Therefore, the objective of this study was to compare the clinical and economic outcomes associated with paclitaxel-cisplatin (PC) and cyclophosphamide-cisplatin (CC) regimens using a pragmatic perspective based on daily clinical practice in a French university hospital. METHOD: A retrospective cost-effectiveness analysis, from the hospital-payer perspective, was carried out as a before-after case study in fifty-nine consecutive women with verified International Federation of Gynaecology and Obstetrics (FIGO) stage II, III or IV ovarian cancer treated between 1995 and 2000. Median overall survival (OS) was used as the primary endpoint. The quality-adjusted time was assessed by the quality-adjusted time without symptoms or toxicity (Q-TWiST) method. Direct medical costs were collected for each patient. Monetary values for French prices in the year 2000 were used and converted to US dollars using an exchange rate of USD 1 = 7 French francs. Several univariate sensitivity analyses were carried out varying unit costs, medical practices and administration of paclitaxel. RESULTS: The incremental cost of the PC regimen was USD 10,716 per patient. OS and quality-adjusted time were improved by 10.8 and 9.3 months with the PC regimen. The cost per life-year gained and per added QALY were USD 11,907 and USD 13,827, respectively. The robustness of the results was confirmed in sensitivity analyses. CONCLUSION: Our study suggests that PC may be a cost-effective regimen for advanced ovarian cancer in a French university hospital setting. We reported higher incremental costs and lower clinical benefits than RCT-based findings, suggesting that RCT-based findings were clearly balanced by our pragmatic approach based on clinical practices. Observational studies can provide complementary and balanced data for decision making.
INTRODUCTION:Paclitaxel plus cisplatin is considered to be the standard first-line therapy for advanced ovarian cancer. Previous to this study, economic data on this combination resulted from randomised clinical trials (RCTs). Therefore, the objective of this study was to compare the clinical and economic outcomes associated with paclitaxel-cisplatin (PC) and cyclophosphamide-cisplatin (CC) regimens using a pragmatic perspective based on daily clinical practice in a French university hospital. METHOD: A retrospective cost-effectiveness analysis, from the hospital-payer perspective, was carried out as a before-after case study in fifty-nine consecutive women with verified International Federation of Gynaecology and Obstetrics (FIGO) stage II, III or IV ovarian cancer treated between 1995 and 2000. Median overall survival (OS) was used as the primary endpoint. The quality-adjusted time was assessed by the quality-adjusted time without symptoms or toxicity (Q-TWiST) method. Direct medical costs were collected for each patient. Monetary values for French prices in the year 2000 were used and converted to US dollars using an exchange rate of USD 1 = 7 French francs. Several univariate sensitivity analyses were carried out varying unit costs, medical practices and administration of paclitaxel. RESULTS: The incremental cost of the PC regimen was USD 10,716 per patient. OS and quality-adjusted time were improved by 10.8 and 9.3 months with the PC regimen. The cost per life-year gained and per added QALY were USD 11,907 and USD 13,827, respectively. The robustness of the results was confirmed in sensitivity analyses. CONCLUSION: Our study suggests that PC may be a cost-effective regimen for advanced ovarian cancer in a French university hospital setting. We reported higher incremental costs and lower clinical benefits than RCT-based findings, suggesting that RCT-based findings were clearly balanced by our pragmatic approach based on clinical practices. Observational studies can provide complementary and balanced data for decision making.
Authors: F M Muggia; P S Braly; M F Brady; G Sutton; T H Niemann; S L Lentz; R D Alvarez; P R Kucera; J M Small Journal: J Clin Oncol Date: 2000-01 Impact factor: 44.544
Authors: M J Piccart; K Bertelsen; K James; J Cassidy; C Mangioni; E Simonsen; G Stuart; S Kaye; I Vergote; R Blom; R Grimshaw; R J Atkinson; K D Swenerton; C Trope; M Nardi; J Kaern; S Tumolo; P Timmers; J A Roy; F Lhoas; B Lindvall; M Bacon; A Birt; J E Andersen; B Zee; J Paul; B Baron; S Pecorelli Journal: J Natl Cancer Inst Date: 2000-05-03 Impact factor: 13.506
Authors: Insiya B Poonawalla; Rohan C Parikh; Xianglin L Du; Helena M VonVille; David R Lairson Journal: Pharmacoeconomics Date: 2015-11 Impact factor: 4.981