a b s t r a c tObjective. There is a need to develop and validate biomarkers for treatment response and survival in tuboovarian high-grade serous carcinoma (HGSC). The chemotherapy response score (CRS) stratifies patients into Gynecologic Oncology 154 (2019) 441-448 complete/near-complete (CRS3), partial (CRS2), and no/minimal (CRS1) response after neoadjuvant chemotherapy (NACT). Our aim was to review current evidence to determine whether the CRS is prognostic in women with tubo-ovarian HGSC treated with NACT.Methods. We established an international collaboration to conduct a systematic review and meta-analysis, pooling individual patient data from 16 sites in 11 countries. Patients had stage IIIC/IV HGSC, 3-4 NACT cycles and N6-months follow-up. Random effects models were used to derive combined odds ratios in the pooled population to investigate associations between CRS and progression free and overall survival (PFS and OS).Results. 877 patients were included from published and unpublished studies. Median PFS and OS were 15 months (IQR 5-65) and 28 months (IQR 7-92) respectively. CRS3 was seen in 249 patients (28%). The pooled hazard ratios (HR) for PFS and OS for CRS3 versus CRS1/CRS2 were 0·55 (95% CI, 0·45-0·66; P b 0·001) and 0·65 (95% CI 0·50-0·85, P = 0·002) respectively; no heterogeneity was identified (PFS: Q = 6·42, P = 0·698, I2 = 0·0%; OS: Q = 6·89, P = 0·648, I2 = 0·0%). CRS was significantly associated with PFS and OS in multivariate models adjusting for age and stage. Of 306 patients with known germline BRCA1/2 status, those with BRCA1/2 mutations (n = 80) were more likely to achieve CRS3 (P = 0·027).Conclusions. CRS3 was significantly associated with improved PFS and OS compared to CRS1/2. This validation of CRS in a real-world setting demonstrates it to be a robust and reproducible biomarker with potential to be incorporated into therapeutic decision-making and clinical trial design.• The Chemotherapy response score (CRS) assesses histological effect in ovarian cancer after neoadjuvant chemotherapy (NACT). • The CRS is associated with progression-free and overall survival.• CRS could provide useful information to estimate a patient's probability of early vs. late relapse.• The CRS is an appealing primary endpoint in clinical trials as a surrogate for survival as it can be measured earlier. • We recommend the CRS be incorporated as an endpoint in clinical trials of novel therapeutic agents that have a NACT arm.

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Entrance and exit doses are commonly measured in in vivo dosimetry for comparison with expected values, usually generated by the treatment planning system (TPS), to verify accuracy of treatment delivery. This report aims to evaluate the accuracy of six TPS algorithms in computing entrance and exit doses for a 6 MV beam. The algorithms tested were: pencil beam convolution (Eclipse PBC), analytical anisotropic algorithm (Eclipse AAA), AcurosXB (Eclipse AXB), FFT convolution (XiO Convolution), multigrid superposition (XiO Superposition), and Monte Carlo photon (Monaco MC). Measurements with ionization chamber (IC) and diode detector in water phantoms were used as a reference. Comparisons were done in terms of central axis point dose, 1D relative profiles, and 2D absolute gamma analysis. Entrance doses computed by all TPS algorithms agreed to within 2% of the measured values. Exit doses computed by XiO Convolution, XiO Superposition, Eclipse AXB, and Monaco MC agreed with the IC measured doses to within 2%‐3%. Meanwhile, Eclipse PBC and Eclipse AAA computed exit doses were higher than the IC measured doses by up to 5.3% and 4.8%, respectively. Both algorithms assume that full backscatter exists even at the exit level, leading to an overestimation of exit doses. Despite good agreements at the central axis for Eclipse AXB and Monaco MC, 1D relative comparisons showed profiles mismatched at depths beyond 11.5 cm. Overall, the 2D absolute gamma (3%/3 mm) pass rates were better for Monaco MC, while Eclipse AXB failed mostly at the outer 20% of the field area. The findings of this study serve as a useful baseline for the implementation of entrance and exit in vivo dosimetry in clinical departments utilizing any of these six common TPS algorithms for reference comparison.PACS numbers: 87.55.‐x, 87.55.D‐, 87.55.N‐, 87.53.Bn