Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study

Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study Mengdi Fu, Chengjuan Jin, Jingying Chen, Shuai Feng, Lekai Nie, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-786505/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jan, 2022 Read the published version in Frontiers in Oncology → Version 1 posted You are reading this latest preprint version Abstract Background Whether neoadjuvant chemotherapy (NAC) followed by interval debulking surgery (IDS) against primary debulking surgery (PDS) has a differential effect on prognosis due to Breast Cancer Susceptibility Genes (BRCA)1/2 mutations has not been confirmed by current studies. Methods All patients included in this retrospective study were admitted to Qilu Hospital of Shandong University between January 2009 and June 2020, and germline BRCA1/2 mutation were tested. Patients in stage IIIB, IIIC, and IV, re-staged by International Federation of Gynecology and Obstetrics (FIGO) 2014, were selected for analysis. All patients with NAC received 1–3 cycles of platinum-containing (carboplatin, cisplatin, or nedaplatin) chemotherapy. Patients who received maintenance therapy after chemotherapy were not eligible for this study. All relevant medical records were collected. Results A total of 308 patients were enrolled in the study, including 108 patients with BRCA1/2 mutations (BRCAmut), and 200 patients with BRCA1/2 wild-type (BRCAwt). In the two groups, 36 BRCAmut patients (33.3%) and 59 BRCAwt patients (29.5%) received neoadjuvant chemotherapy. The progression-free survival (PFS) of BRCAmut patients was significantly reduced after NAC (median: 15.0 vs. 19.0 months, HR = 0.59; p = 0.03); however, there was no statistical difference in overall survival (OS) (median: 75.1 vs. 68.5 months, HR = 0.90; p = 0.72). Whether BRCAwt patients received NAC had no significant effect on PFS (median: 13.5 vs. 14.6 months, HR = 1.02; p = 0.90) or OS (median: 54.0 vs. 56.4 months, HR = 1.23; p = 0.34). Multivariate analyses showed that the independent predictors of prolonged survival were PDS (p = 0.003), the absence of residual tumor after surgery (p = 0.010), and FIGO III stage (p = 0.011). Conclusions For advanced-stage ovarian cancer patients treated with NAC followed by IDS, PFS and OS were not significantly affected in BRCAwt patients. In BRCAmut patients, NAC-IDS resulted in a shortened PFS, but had no further effect on overall survival. Sexual & Reproductive Medicine Cancer Biology Neoadjuvant chemotherapy primary debulking surgery BRCA prognosis Figures Figure 1 Figure 2 Figure 3 Background Ovarian cancer is the most lethal gynecological malignancy. According to the 2021 Cancer Statistics Report published by the American Cancer Society, there will be an estimated 21,410 new ovarian cancer cases and 13,770 deaths in the United States in 2021[ 1 ]. Ovarian cancer has no typical clinical symptoms in its early stage, and there is no effective screening method; therefore, the vast majority of patients have reached the advanced stage at diagnosis, leading to poor prognoses[ 2 ].For patients with FIGO stage III/IV, the maximum cytoreductive surgery (R1, residual lesions less than 1 cm; R0, no residual lesions) is the most critical factor affecting the prognosis[ 3 – 5 ]; however, if it is difficult to remove metastatic lesions in the intestine, spleen, liver or abdominal para-aortic lymph nodes due to extensive tumor metastasis, not all patients can achieve satisfactory resection from primary debulking surgery (PDS). Therefore, neoadjuvant chemotherapy (NAC) followed by interval debulking surgery (IDS) can be used as an alternative treatment to achieve maximum resection of lesions. To date, several clinical trials have confirmed that there was no significant difference between NAC-IDS and PDS in the prognoses of ovarian cancer patients[ 6 – 8 ]. The discovery of the BRCA1/2 mutations is one of the milestones in the treatment of ovarian cancer. Ovarian cancer patients with BRCA1/2 mutations (BRCAmut), compared with BRCA1/2 wild-type (BRCAwt) patients, have a higher efficacy of platinum-based chemotherapy, a longer recurrence interval due to the presence of homologous recombination defects, and maintain a higher response rate to platinum-based chemotherapy after recurrence[ 9 , 10 ]. In addition, based on the synthetic lethal theory of poly (ADP-ribose) polymerase inhibitor (PARPi), BRCAmut patients have significantly prolonged survival in salvage therapy and maintenance therapy with PARPi[ 11 , 12 ]. Thus, the treatment of ovarian cancer patients can be divided into two groups based on the mutational status of BRCA1/2. Whether NAC followed by IDS has a differential effect on prognosis due to BRCA1/2 mutations has not been confirmed by current studies; therefore, we conducted this retrospective study to explore the effect of BRCA1/2 mutations on neoadjuvant chemotherapy. Methods Patients and clinical data All patients included in this retrospective study were admitted to Qilu Hospital of Shandong University between January 2009 and June 2020. A flowchart of this study is presented in Fig. 1. Patients were re-staged according to FIGO2014, and patients in stage IIIB, IIIC, and IV were selected for analysis. All patients with NAC received 1–3 cycles of platinum-containing (carboplatin, cisplatin, or nedaplatin) chemotherapy. Patients who received only one cycle of NAC were eligible only if the sum of lesions decreased by more than 30% according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria[ 13 ]. Patients who received maintenance therapy after chemotherapy, such as PARP inhibitors or bevacizumab, were not eligible for this study. The determination of response and progression-free survival (PFS) were in accordance with RECIST criteria; if the data for the RECIST criteria were not complete, CA-125 level was used as an alternative, only if the pretreatment level was at least twice the upper limit of normal[ 13 ]. Relevant medical data collected from patients included: age, the serum cancer antigen (CA) 125 level at diagnosis, maximum diameter of primary lesion, regimens and cycles of NAC, changes of the maximum diameter of primary lesions and sum of target lesions based on RECIST standard after NAC, hematological toxicity of NAC based on Common Terminology Criteria for Adverse Events (CTCAE) 5.0, operative duration, hemorrhage volume, residual lesions, pathological types, postoperative chemotherapy regimens, cycles and hematological toxicity, history of PARP inhibitors, FPS and OS. Germline BRCA1/2 testing The BRCA1/2 genetic testing panels used for detection covered the entire coding sequences of the BRCA1 and BRCA2 gene, including 10–50 bases of adjacent intronic sequences of each exon. Sequencing was performed on next generation sequence (NGS) platform according to Illumina’s protocol. Sanger DNA sequencing using specific gene primers was performed to confirm each reported variant. Multiplex ligation-dependent probe amplification was used to detect BRCA 1/2 large fragment rearrangements. The variants of the mutations were classified according to the 5-class classification standard[ 14 ]. Statistical methods Student’s t-test was used to compare the differences in continuous variables. The chi-square test was performed to analyze differences in clinical characteristics. PFS and OS analyses were performed by Kaplan-Meier method. Multivariate proportional odds models were used to identify variables associated with PFS outcome of BRCAmut group, and hazard ratios (HR) with 95% confidence intervals (CI) were calculated. All statistical analyses were performed by Prism 8 version 8.4.0. Significance levels were *p < 0.05, **p < 0.01. Results Characteristics of the Patients and Treatment Received Between January 2009 and June 2020, 705 ovarian cancer patients underwent germinal BRCA1/2 gene test. There were 308 patients enrolled in the study, including 108 BRCAmut patients and 200 BRCAwt patients. In the two groups, 36 patients (33.3%) and 59 patients (29.5%) received NAC, respectively, with no statistical difference (p = 0.49). All patients received carboplatin, cisplatin, or nedaplatin based chemotherapy. The chemotherapy regimens and NAC cycles are shown in Table 1 . Table 1 Chemotherapy regimens of Patients. Characteristic BRCAmut BRCAwt Chemotherapy regimens of NAC Carboplatin based 23 (63.9%) 24 (40.7%) Cisplatin based 10 (27.8%) 23 (39.0%) Nedaplatin based 1 (2.8%) 2 (3.4%) Multiple platinum 2 (5.6%) 8 (13.6%) Unknown 0 (0%) 2 (3.4%) Cycle of NAC 1 6 (16.7%) 10 (16.9%) 2 18 (50.0%) 28 (47.5%) 3 12 (33.3%) 21 (35.6%) Chemotherapy regimens after surgery of NAC-IDS Carboplatin based 23 (63.9%) 25 (42.4%) Cisplatin based 5 (13.9%) 13 (22.0%) Nedaplatin based 1 (2.8%) 7 (11.9%) Multiple platinum 7 (19.4%) 12 (20.3%) Unknown 0 (0%) 2 (3.4%) Chemotherapy regimens after surgery of PDS Carboplatin based 37 (51.4%) 77 (54.6%) Cisplatin based 15 (20.8%) 25 (17.7%) Nedaplatin based 3 (4.2%) 4 (2.8%) Multiple platinum 15 (20.8%) 32 (22.7%) Unknown 2 (2.8%) 3 (2.1%) The characteristics of the patients were shown in Tables 2 and 3 . Among BRCAmut patients receiving NAC-IDS and PDS, the median ages at diagnosis were 53 years (range: 34–71) and 52 years (range: 34–79), respectively, with no significant difference. The pathological types of patients in both groups were mainly high-grade serous carcinoma (91.7% and 94.4%, respectively), and the proportion of the maximum volume of primary lesions at diagnosis was similar. The proportion of CA125 above 1000U/ml in patients with NAC was higher than patients with PDS (58.3% vs. 30.6%, p = 0.002). After receiving NAC, the largest primary lesions in 75.0% of patients were reduced to less than 5cm; before chemotherapy, the proportion was only 13.9%. The operative time of patients in the two groups were similar, with a median of 155min (range: 80-370min) and 155min (range: 75-600min), respectively. However, the amount of blood loss in patients receiving NAC was significantly reduced than patients with PDS (300, range 100-1000ml vs. 400, rang 100-2000ml; p = 0.044). Moreover, NAC significantly increased the proportion of R0 excisions (55.5% vs. 27.8%; p = 0.004). For adverse reactions, the most common hematologic toxicities (CTCAE ≥ 3) were neutrophil count decreased and white blood cell count decreased, which were 22.2% and 19.4% in the neoadjuvant patients. The proportion of postoperative hematologic toxicities in the two groups was similar (p = 0.644). In addition, it is worth noting that 52% of BRCAmut patients were treated with PARP inhibitors in the posterior lines of treatment. Table 2 Baseline Characteristics of the BRCAmut Patients. Characteristic Neoadjuvant Chemotherapy (N = 36) Primary Debulking Surgery (N = 72) P value Age (years) Median 53 52 0.878 Range 34–71 34–79 Histologic type — no. (%) High-grade serous 33 (91.7%) 68 (94.4%) NA Low-grade serous 0 (0%) 1 (1.4%) Serous not specified 1 (2.8%) 3 (4.2%) Mucinous 0 (0%) 0 (0%) Clear-cell 2 (5.6%) 0 (0%) Endometrioid 0 (0%) 0 (0%) Mixed 0 (0%) 0 (0%) Stage — no. (%) IIIB/IIIC 32 (88.9%) 62 (86.1%) 0.685 IVa/IVb 4 (11.1%) 10 (13.9%) Largest primary tumor at diagnosed (cm)— no. (%) ≤ 5 5 (13.9%) 11 (15.3%) 0.829 > 5, ≤ 10 18 (50.0%) 38 (52.8%) > 10, ≤ 15 4 (11.1%) 14 (19.4%) > 15 1 (2.8%) 4 (5.6%) Unknown 8 (22.2) 5 (6.9%) Largest primary tumor before surgery (cm)— no. (%) ≤ 5 27 (75.0%) NA NA > 5, ≤ 10 8 (22.2%) NA > 10, ≤ 15 0 (0%) NA > 15 0 (0%) NA Unknown 1 (2.8%) NA Serum CA-125(U/ml) ≤ 1000 8 (22.2%) 36 (50.0%) 0.002 ** > 1000 21 (58.3%) 22 (30.6%) Unknown 7 (19.4%) 14 (19.4%) Residual lesions (cm) 0 20 (55.5%) 20 (27.8%) 0.004 ** < 1 6 (16.7%) 33 (45.8%) ≥ 1 7 (19.4%) 17 (23.6%) Unknown 3 (8.3%) 2 (2.8%) Duration of Operation(min) Median 155 155 0.344 Range 80–370 75–600 Hemorrhage of Operation (ml) Media 300 400 0.044 * Range 100–1000 100–2000 Response of NAC PR/CR 21 (58.3%) NA SD/PD 7 (19.4%) NA Unknown 8 (22.2%) NA History of PARPi Yes 20 (55.6%) 42 (58.3%) 0.783 No/Unknown 16 (44.4%) 30 (41.7%) Hematologic toxicity of NAC (≥ 3 CTCAE) White blood cell decreased 7 (19.4%) NA NA Neutrophil decreased 8 (22.2%) NA Anemia 1 (2.8%) NA Platelet decreased 1 (2.8%) NA Hematologic toxicity after surgery (≥ 3 CTCAE) White blood cell decreased 7 (19.4%) 11 (15.3%) 0.644 Neutrophil decreased 10 (27.8%) 27 (37.5%) Anemia 3 (8.3%) 3 (4.2%) Platelet decreased 1 (2.8%) 2 (2.8%) Table 3 Baseline Characteristics of the BRCAwt Patients. Characteristic Neoadjuvant Chemotherapy (N = 59) Primary Debulking Surgery (N = 141) P value Age (years) Median 56 53 0.107 Range 23–75 26–73 Histologic type — no. (%) High-grade serous 53 (89.8%) 120 (85.1%) NA Low-grade serous 2 (3.4%) 5 (3.5%) Serous not specified 3 (5.1%) 3 (2.1%) Mucinous 0 (0%) 4 (2.8%) Clear-cell 1 (1.7%) 3 (2.1%) Endometrioid 0 (0%) 5 (3.5%) Mixed 0 (0%) 1 (0.7%) Stage — no. (%) IIIB/IIIC 50 (84.7%) 131 (92.9%) 0.073 IVa/IVb 9 (15.3%) 10 (7.1%) Largest tumor at diagnosed (cm)— no. (%) ≤ 5 7 (11.9%) 23 (16.3%) 0.962 > 5, ≤ 10 27 (45.8%) 69 (48.9%) > 10, ≤ 15 12 (20.3%) 32 (22.7%) > 15 3 (5.1%) 9 (6.4%) Unknown 10 (16.9%) 8 (5.7%) Largest tumor before surgery (cm)— no. (%) ≤ 5 36 (61.0%) NA NA > 5, ≤ 10 13 (22.0%) NA > 10, ≤ 15 4 (6.8%) NA > 15 2 (3.4%) NA Unknown 4 (6.8%) NA Serum CA-125(U/ml) ≤ 1000 18 (30.5%) 76 (53.9%) 0.019 * > 1000 26 (44.1%) 48 (34.0%) Unknown 15 (25.4%) 17 (12.1%) Residual lesions (cm) 0 25 (42.4%) 40 (28.4%) 0.034 * ≤ 1 23 (39.0%) 56 (39.7%) > 1 7 (11.9%) 38 (27.0%) Unknown 4 (6.8%) 7 (5.0%) Duration of Operation(min) Median 145 155 0.758 Range 70–600 75–550 Hemorrhage of Operation (ml) Media 300 400 0.019 * Range 60-1500 100–6000 Response of NAC PR/CR 24 (40.7%) NA SD/PD 24 (40.7%) NA Unknown 11 (18.6%) NA Hematologic toxicity of NAC (≥ 3 CTCAE) White blood cell decreased 5 (8.5%) NA NA Neutrophil decreased 9 (15.3%) NA Anemia 4 (6.8%) NA Platelet decreased 0 (0%) NA Hematologic toxicity after surgery (≥ 3 CTCAE) White blood cell decreased 7 (11.9%) 27 (19.1%) 0.858 Neutrophil decreased 11 (18.6%) 42 (29.8%) Anemia 2 (3.4%) 4 (2.8%) Platelet decreased 1 (1.7%) 2 (1.4%) The median age at diagnosis was slightly higher in BRCAwt patients in both NAC-IDS and PDS group (56 and 53 years, respectively) compared to BRCAmut patients. The pathological type was dominated by high-grade serous carcinoma, and the proportion was similar between NAC-IDS and PDS groups. The proportion of FIGO stage III patients (84.7% vs. 92.9%, p = 0.073) and surgical duration (median 145 vs. 155 min, p = 0.758) were also similar between the two groups. There was no statistical difference in the proportion of the largest primary lesion. As in BRCAmut patients, the proportion of BRCAwt patients receiving NAC with ca125 level above 1000u/ml (44.1% vs. 34.0%; p = 0.019) and the R0 resection rate (42.4% vs. 28.4%; p = 0.034) were higher than those in PDS patients; however, the blood loss was significantly reduced (median 300 ml, range 60-1500ml vs. median 400ml, range 100-6000ml; p = 0.019). The hematologic toxicity of NAC in BRCAwt patients was similar to that of BRCAmut, and there was no statistical difference in postoperative hematologic toxicity between NAC-IDS and PDS group (p = 0.858). Finally, BRCAwt patients did not respond as significantly to NAC as BRCAmut; among the evaluable patients, the ratios of partial response (PR) were 50.0% (24/48) and 75.0% (21/28), respectively (p = 0.03). Effect of neoadjuvant chemotherapy on PFS and OS Regardless of the BRCA1/2 mutational status, there were no statistical differences in prognoses between patients in the NAC-IDS and PDS groups for PFS, (median: 15.4 vs. 14.9 months, HR = 0.84; p = 0.19) (Fig. 2A) or OS (median: 57.1 vs. 64.7 months, HR = 1.11; p = 0.56) (Fig. 3A). Further analysis found that the PFS of BRCAmut patients was significantly reduced after NAC (median, 15.0 vs. 19.0months, HR = 0.59; p = 0.03) (Fig. 2B); however, there was no statistical difference in OS (median, 75.1 vs. 68.5months, HR = 0.90; p = 0.72) (Fig. 3B). Whether BRCAwt patients received NAC had no significant effect on PFS (median, 13.5 vs. 14.6 months, HR = 1.02; p = 0.90) (Fig. 2C) and OS (median, 54.0 vs. 56.4 months, HR = 1.23; p = 0.34) (Fig. 3C). Cox regression multivariate analyses were performed, with PFS as the endpoint, and included the following variables: age at diagnosis, residual lesions, largest primary tumor size, FIGO stage, NAC-IDS or not, and CA-125 level. The strongest independent predictors of prolonged survival, in descending order PDS (p = 0.003), were the absence of residual tumor after surgery (p = 0.010) and FIGO III disease (p = 0.011). The other variables did not significantly influence PFS (Table 4 ). Table 4 Multivariate analysis of prognostic markers related to PFS in BRCAmut patients Item PFS HR(95% Cl) p -value FIGO (III / IV) 0.397(0.194–0.811) 0.011 * NAC-IDS (No / Yes) 0.393(0.211–0.732) 0.003 ** Residual Lesions(R0 / R1 + R2) 0.490(0.285–0.840) 0.010 * CA-125 (≤ 1000 / >1000 U/ml) 0.794(0.464–1.359) 0.401 Age(≤50 / >50 years) 0.887 (0.522–1.507) 0.887 Maximum of Lesions (≤ 10 / >10 cm) 0.636(0.345–1.171) 0.146 Discussion In this retrospective study, we found that without considering the BRCA1/2 mutation status, both PFS and OS after neoadjuvant chemotherapy followed by interval debulking surgery were similar to survivals with primary surgery followed by chemotherapy, which was consistent with the conclusions of previous randomized controlled trials[ 8 , 15 ]. In BRCAmut patients, NAC-IDS significantly shortened PFS, however, it had no effect on OS. For BRCAwt patients, NAC did not significantly affect the prognosis. To our knowledge, this is the first retrospective study to date to discuss the effect of NAC on prognosis based on the BRCA mutational status. The proportion of patients with BRCA1/2 mutations was 35.1%, which is much higher than that previously reported in the literature[ 16 – 18 ]. This could be related to the fact that all patients included in the study were at an advanced stage. Both BRCA1 and BRCA2 are tumor suppressor genes, and their functional proteins play an important role in DNA homologous recombinant double-stranded break repair. In the absence of functional BRCA1/2 gene, tumor cells are more aggressive and therefore more prone to distant metastasis, leading to an increased proportion of patients with FIGO III and IV stage[ 19 ]. According to previous reports, the highest proportion of BRCA1/2 mutation in Chinese ovarian cancer patients was 28.5%. However, if stage III and IV patients were separately counted, the proportion of patients with BRCA1/2 mutation was significantly increased in these studies[ 16 , 18 ]. The primary evaluation criteria for the initial treatment of advanced ovarian cancer patients is whether satisfactory cytoreductive surgery can be achieved in PDS, especially R0 resection, which could significantly prolong survival[ 20 ]. At present, clinical practice guidelines and expert consensus suggest that NAC is recommended for FIGO stage III to IV patients with poor physical status and unable to tolerate surgery, and for patients in whom it is difficult to achieve satisfactory tumor cytoreductive surgery (R0 and R1)[ 20 – 22 ]. Several studies have confirmed that the serum CA-125 level was an important predictor of surgical outcome, defined as successful cytoreductive surgery with a residual tumor ≤ 1 cm, and is a significant factor in decision-making regarding the proper selection for PDS or NAC[ 23 – 25 ]. In our study, the largest primary lesion at diagnosis was similar in both the NAC and PDS groups regardless of BRCA mutation, but the CA-125 levels in patients receiving NAC were significantly higher than those in the PDS group, which is one of the important reasons for choosing NAC. In addition, NAC can significantly increase the proportion of R0 resection and reduce the amount of bleeding during surgery, consistent with the conclusions of previous reports[ 6 , 15 ]. Although R0 resection rates were significantly improved in both BRCAmut and BRCAwt patients receiving NAC, the OS did not improve, nor did PFS in BRCAwt patients. In contrast, in BRCAmut patients, NAC significantly shortened PFS; further multivariate analysis found that NAC-IDS, FIGO IV stage, and R1/R2 resection were risk factors for poor PFS. Compared with BRCAwt patients, BRCAmut patients previously showed a significantly increased peritoneal tumor load[ 26 ], were associated with nodular peritoneal disease pattern[ 27 ], and showed increased sensitivity to NAC[ 28 ]. In our study, the proportion of BRCAmut patients who achieved partial response after neoadjuvant chemotherapy was 75.0%, which was significantly higher than that of BRCAwt patients (50%). The above reasons could cause more peritoneal lesions to become invisible after NAC and, thus, cannot be completely resected; therefore, R0 resection may not be truly achieved; instead, the complete response (CR) status was achieved through chemotherapy, which may be the main reason for reduced PFS in BRCAmut patients. BRCA1/2 genes are tumor suppressors, that play an important role in DNA damage repair and normal cell growth. BRCA1/2 mutations can inhibit the repair of DNA damage, resulting in homologous recombination deficiency, which eventually lead to carcinogenesis[ 29 ]. In BRCA1/2 mutated tumor cells, DNA double-stranded repair function is lost; since PARP inhibitors can block single-stranded DNA repair, this results in a "synthetic lethal" effect that leads to the death of tumor cells[ 9 ]. Therefore, PARP inhibitors have excellent maintenance treatment effects in BRCAmut patients, which can significantly prolong the PFS and OS[ 30 , 31 ]. In the SOLO-2 clinical trial of olaparib[ 32 ], maintenance therapy with olaparib in BRCAmut platinum-sensitive relapse patients extended the relapse time by 24.7 months and reduced the risk of recurrence or death by 70%. In addition, the objective response rate in BRCAmut patients with platinum-sensitive relapses above three lines was about 70% when treated with PARP inhibitors[ 12 ]. The evaluation of PFS in our study, although excluding patients with PARP inhibitors for maintenance therapy, there were a large number of patients treated with PARP inhibitors in the posterior line of treatment. This is probably the main reason for the subsequent overall survival consistency. This retrospective study had several limitations. First, several studies have suggested that surgery is appropriate after three cycles of NAC[ 6 , 8 , 21 ]. Patients with 1–3 cycles were included in our study; however, patients with one cycle of chemotherapy, were not suitable if PR was not achieved, which may affect the prognosis to some extent. In addition, we did not collect details of patients using PARP inhibitors in the posterior line; therefor, no further analysis of OS was performed to exclude the effect of PARP inhibitors. Conclusion In conclusion, for advanced-stage ovarian cancer patients treated with NAC followed by IDS, PFS and OS were not significantly affected in BRCAwt patients. In BRCAmut patients, NAC-IDS resulted in a shortened PFS, but had no further effect on OS. Additional randomized controlled trials will be necessary to elucidate the effect of BRCA1/2 mutation on prognoses of advanced-stage ovarian cancer patients. Abbreviations NAC: Neoadjuvant chemotherapy; IDS: Interval debulking surgery; PDS: Primary debulking surgery; BRCA: Breast Cancer Susceptibility Genes; FIGO: International Federation of Gynecology and Obstetrics; PFS: Progression-free survival; OS: Overall survival; PAPR: Poly (ADP‐ribose) polymerase; RECIST: Response evaluation criteria in solid tumors; NGS: Next generation sequence; HR: Hazard ratios; CI: Confidence intervals; CA125: cancer antigen 125; CTCAE: Common Terminology Criteria for Adverse Events. Declarations Ethics approval and consent to participate The study was approved by the ethics committee of Qilu Hospital of Shandong University, and informed consents were obtained from all patients. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by Department of Science Technology of Jinan city (No. 201705051). Authors' contributions Mengdi Fu: Conceptualization, investigation, methodology, project administration, and writing‐original draft. Chengjuan Jin: Data curation, formal analysis, and software. Jingying Chen, Shuai Feng, Lekai Nie, Xia Wang, and Yang Zhang: Data curation. Jin Peng: Funding acquisition, investigation and methodology. Hualei Bu and Beihua Kong: Formal analysis, methodology, supervision, validation, review, and editing. All authors have reviewed and approved the final manuscript. Acknowledgements Not applicable. References Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics. 2021. 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Bolton KL, Chenevix-Trench G, Goh C, Sadetzki S, Ramus SJ, Karlan BY, et al. Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer. JAMA. 2012;307:382–90. Colombo N, Sessa C, du Bois A, Ledermann J, McCluggage WG, McNeish I, et al. ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent diseasedagger. Ann Oncol. 2019;30:672–705. Wright AA, Bohlke K, Armstrong DK, Bookman MA, Cliby WA, Coleman RL, et al. Neoadjuvant Chemotherapy for Newly Diagnosed, Advanced Ovarian Cancer: Society of Gynecologic Oncology and American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol. 2016;34:3460–73. Suh DH, Chang SJ, Song T, Lee S, Kang WD, Lee SJ, et al. Practice guidelines for management of ovarian cancer in Korea: a Korean Society of Gynecologic Oncology Consensus Statement. J Gynecol Oncol. 2018;29:e56. Arab M, Jamdar F, Sadat Hosseini M, Ghodssi- Ghasemabadi R, Farzaneh F, Ashrafganjoei T. Model for Prediction of Optimal Debulking of Epithelial Ovarian Cancer. Asian Pac J Cancer Prev. 2018;19:1319–24. Saygili U, Guclu S, Uslu T, Erten O, Demir N, Onvural A. Can serum CA-125 levels predict the optimal primary cytoreduction in patients with advanced ovarian carcinoma? Gynecol Oncol. 2002;86:57–61. Gemer O, Lurian M, Gdalevich M, Kapustian V, Piura E, Schneider D, et al. A multicenter study of CA 125 level as a predictor of non-optimal primary cytoreduction of advanced epithelial ovarian cancer. Eur J Surg Oncol. 2005;31:1006–10. Petrillo M, Marchetti C, De Leo R, Musella A, Capoluongo E, Paris I, et al. BRCA mutational status, initial disease presentation, and clinical outcome in high-grade serous advanced ovarian cancer: a multicenter study. Am J Obstet Gynecol. 2017;217:334. e1- e9. Nougaret S, Lakhman Y, Gonen M, Goldman DA, Micco M, D'Anastasi M, et al. High-Grade Serous Ovarian Cancer: Associations between BRCA Mutation Status, CT Imaging Phenotypes, and Clinical Outcomes. Radiology. 2017;285:472–81. Gorodnova TV, Sokolenko AP, Ivantsov AO, Iyevleva AG, Suspitsin EN, Aleksakhina SN, et al. High response rates to neoadjuvant platinum-based therapy in ovarian cancer patients carrying germ-line BRCA mutation. Cancer Lett. 2015;369:363–7. Konstantinopoulos PA, Ceccaldi R, Shapiro GI, D'Andrea AD. Homologous Recombination Deficiency: Exploiting the Fundamental Vulnerability of Ovarian Cancer. Cancer Discov. 2015;5:1137–54. Moore K, Colombo N, Scambia G, Kim BG, Oaknin A, Friedlander M, et al. Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer. N Engl J Med. 2018;379:2495–505. Essel KG, Moore KN. Niraparib for the treatment of ovarian cancer. Expert Rev Anticancer Ther. 2018;18:727–33. Pujade-Lauraine E, Ledermann JA, Selle F, Gebski V, Penson RT, Oza AM, et al. Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18:1274–84. Cite Share Download PDF Status: Published Journal Publication published 06 Jan, 2022 Read the published version in Frontiers in Oncology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-786505","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":44493263,"identity":"b8084146-f212-445c-acc2-381aa3a57de2","order_by":0,"name":"Mengdi Fu","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mengdi","middleName":"","lastName":"Fu","suffix":""},{"id":44493264,"identity":"f8cad607-cce9-4893-a549-38d3a2691ae9","order_by":1,"name":"Chengjuan Jin","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chengjuan","middleName":"","lastName":"Jin","suffix":""},{"id":44493265,"identity":"e42ec26e-328f-4d21-8ed6-4b96bc3743ef","order_by":2,"name":"Jingying Chen","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jingying","middleName":"","lastName":"Chen","suffix":""},{"id":44493266,"identity":"49557654-c475-412c-9100-805d2b442ba6","order_by":3,"name":"Shuai Feng","email":"","orcid":"","institution":"Shandong Cancer Hospital: Shandong Cancer Hospital and Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shuai","middleName":"","lastName":"Feng","suffix":""},{"id":44493267,"identity":"4fa36d38-fdeb-489b-8754-f85375537177","order_by":4,"name":"Lekai Nie","email":"","orcid":"","institution":"Qilu Hospital of Shandong University Qingdao","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lekai","middleName":"","lastName":"Nie","suffix":""},{"id":44493268,"identity":"5b7fb68a-ab27-4204-a75d-c6139160de06","order_by":5,"name":"Yang Zhang","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Zhang","suffix":""},{"id":44493269,"identity":"89dae017-a5ef-455e-ae87-c2cbb864974e","order_by":6,"name":"Jin Peng","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Peng","suffix":""},{"id":44493270,"identity":"45c5ea6f-09d9-436c-9581-2b34ebc8c054","order_by":7,"name":"Xia Wang","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Wang","suffix":""},{"id":44493271,"identity":"c45dbfc1-e945-477d-96b5-f5462f5bdc50","order_by":8,"name":"Hualei Bu","email":"","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hualei","middleName":"","lastName":"Bu","suffix":""},{"id":44493272,"identity":"f1c9dfc7-6ab9-4b10-aa79-b55eb0867753","order_by":9,"name":"Beihua Kong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYBACCSBmBlIJQOrAgQ8VpGlhSzw44wzxWhiAWniMD/O2EKFFsr338OuCCos8g+NnPhzgbWCQ5xc7gF+LNM+5NOsZZySKDc7kbjgguYPBcObsBPxa5CRyzIx52yQSNxwAajE8w5BgcJsoLf+AWs6/eXAgsY0ILdISOcaPeRuAWm7kMBw4SIwWyZ4zZswzjkkkzrzxzOBgwxkJwn6RON5j/Lmgpi6x73zy489/Kmzk+aUJaAECNglkIwgqBwHmD0QpGwWjYBSMgpELAPA8SmxBvHlNAAAAAElFTkSuQmCC","orcid":"","institution":"Shandong University Qilu Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Beihua","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2021-08-06 10:31:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-786505/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-786505/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.3389/fonc.2021.810099","type":"published","date":"2022-01-06T06:31:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":12288180,"identity":"7eb12179-5dc9-42e6-ac14-4e813b3ee048","added_by":"auto","created_at":"2021-08-10 14:53:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":115399,"visible":true,"origin":"","legend":"Flowchart","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-786505/v1/786b25bb5eb6ace1602619af.png"},{"id":12288183,"identity":"0110c0f7-fe3b-4aeb-8665-4545179ef231","added_by":"auto","created_at":"2021-08-10 14:53:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":203613,"visible":true,"origin":"","legend":"PDS groups for PFS, (median: 15.4 vs. 14.9 months, HR=0.84; p=0.19) (Figure 2A) or OS (median: 57.1 vs. 64.7 months, HR=1.11; p=0.56) (Figure 3A). Further analysis found that the PFS of BRCAmut patients was significantly reduced after NAC (median, 15.0 vs. 19.0months, HR=0.59; p=0.03) (Figure 2B); however, there was no statistical difference in OS (median, 75.1 vs. 68.5months, HR=0.90; p=0.72) (Figure 3B). Whether BRCAwt patients received NAC had no significant effect on PFS (median, 13.5 vs. 14.6 months, HR=1.02; p=0.90) (Figure 2C) and OS (median, 54.0 vs. 56.4 months, HR=1.23; p=0.34) (Figure 3C).","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-786505/v1/52b3068effcdb18b3367e622.png"},{"id":12288197,"identity":"3f1bbf3f-3ea7-4d3f-9125-301f9f8ab271","added_by":"auto","created_at":"2021-08-10 14:54:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":194147,"visible":true,"origin":"","legend":"PDS groups for PFS, (median: 15.4 vs. 14.9 months, HR=0.84; p=0.19) (Figure 2A) or OS (median: 57.1 vs. 64.7 months, HR=1.11; p=0.56) (Figure 3A). Further analysis found that the PFS of BRCAmut patients was significantly reduced after NAC (median, 15.0 vs. 19.0months, HR=0.59; p=0.03) (Figure 2B); however, there was no statistical difference in OS (median, 75.1 vs. 68.5months, HR=0.90; p=0.72) (Figure 3B). Whether BRCAwt patients received NAC had no significant effect on PFS (median, 13.5 vs. 14.6 months, HR=1.02; p=0.90) (Figure 2C) and OS (median, 54.0 vs. 56.4 months, HR=1.23; p=0.34) (Figure 3C).","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-786505/v1/7120f54453e809e21d1e28c6.png"},{"id":17043454,"identity":"b771ebac-55bd-4686-83fc-37d3e5eea1e2","added_by":"auto","created_at":"2022-01-06 06:31:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":859653,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-786505/v1/8ebf0502-2e7e-4bb7-8b09-9b6ce05adb87.pdf"}],"financialInterests":"","formattedTitle":"Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study","fulltext":[{"header":"Background","content":"\u003cp\u003eOvarian cancer is the most lethal gynecological malignancy. According to the 2021 Cancer Statistics Report published by the American Cancer Society, there will be an estimated 21,410 new ovarian cancer cases and 13,770 deaths in the United States in 2021[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Ovarian cancer has no typical clinical symptoms in its early stage, and there is no effective screening method; therefore, the vast majority of patients have reached the advanced stage at diagnosis, leading to poor prognoses[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].For patients with FIGO stage III/IV, the maximum cytoreductive surgery (R1, residual lesions less than 1 cm; R0, no residual lesions) is the most critical factor affecting the prognosis[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]; however, if it is difficult to remove metastatic lesions in the intestine, spleen, liver or abdominal para-aortic lymph nodes due to extensive tumor metastasis, not all patients can achieve satisfactory resection from primary debulking surgery (PDS). Therefore, neoadjuvant chemotherapy (NAC) followed by interval debulking surgery (IDS) can be used as an alternative treatment to achieve maximum resection of lesions. To date, several clinical trials have confirmed that there was no significant difference between NAC-IDS and PDS in the prognoses of ovarian cancer patients[\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe discovery of the BRCA1/2 mutations is one of the milestones in the treatment of ovarian cancer. Ovarian cancer patients with BRCA1/2 mutations (BRCAmut), compared with BRCA1/2 wild-type (BRCAwt) patients, have a higher efficacy of platinum-based chemotherapy, a longer recurrence interval due to the presence of homologous recombination defects, and maintain a higher response rate to platinum-based chemotherapy after recurrence[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In addition, based on the synthetic lethal theory of poly (ADP-ribose) polymerase inhibitor (PARPi), BRCAmut patients have significantly prolonged survival in salvage therapy and maintenance therapy with PARPi[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, the treatment of ovarian cancer patients can be divided into two groups based on the mutational status of BRCA1/2. Whether NAC followed by IDS has a differential effect on prognosis due to BRCA1/2 mutations has not been confirmed by current studies; therefore, we conducted this retrospective study to explore the effect of BRCA1/2 mutations on neoadjuvant chemotherapy.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and clinical data\u003c/h2\u003e \u003cp\u003eAll patients included in this retrospective study were admitted to Qilu Hospital of Shandong University between January 2009 and June 2020. A flowchart of this study is presented in Fig.\u0026nbsp;1. Patients were re-staged according to FIGO2014, and patients in stage IIIB, IIIC, and IV were selected for analysis. All patients with NAC received 1\u0026ndash;3 cycles of platinum-containing (carboplatin, cisplatin, or nedaplatin) chemotherapy. Patients who received only one cycle of NAC were eligible only if the sum of lesions decreased by more than 30% according to Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 criteria[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Patients who received maintenance therapy after chemotherapy, such as PARP inhibitors or bevacizumab, were not eligible for this study. The determination of response and progression-free survival (PFS) were in accordance with RECIST criteria; if the data for the RECIST criteria were not complete, CA-125 level was used as an alternative, only if the pretreatment level was at least twice the upper limit of normal[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRelevant medical data collected from patients included: age, the serum cancer antigen (CA) 125 level at diagnosis, maximum diameter of primary lesion, regimens and cycles of NAC, changes of the maximum diameter of primary lesions and sum of target lesions based on RECIST standard after NAC, hematological toxicity of NAC based on Common Terminology Criteria for Adverse Events (CTCAE) 5.0, operative duration, hemorrhage volume, residual lesions, pathological types, postoperative chemotherapy regimens, cycles and hematological toxicity, history of PARP inhibitors, FPS and OS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eGermline BRCA1/2 testing\u003c/h2\u003e \u003cp\u003eThe BRCA1/2 genetic testing panels used for detection covered the entire coding sequences of the BRCA1 and BRCA2 gene, including 10\u0026ndash;50 bases of adjacent intronic sequences of each exon. Sequencing was performed on next generation sequence (NGS) platform according to Illumina\u0026rsquo;s protocol. Sanger DNA sequencing using specific gene primers was performed to confirm each reported variant. Multiplex ligation-dependent probe amplification was used to detect BRCA 1/2 large fragment rearrangements. The variants of the mutations were classified according to the 5-class classification standard[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cp\u003eStudent\u0026rsquo;s t-test was used to compare the differences in continuous variables. The chi-square test was performed to analyze differences in clinical characteristics. PFS and OS analyses were performed by Kaplan-Meier method. Multivariate proportional odds models were used to identify variables associated with PFS outcome of BRCAmut group, and hazard ratios (HR) with 95% confidence intervals (CI) were calculated. All statistical analyses were performed by Prism 8 version 8.4.0. Significance levels were *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of the Patients and Treatment Received\u003c/h2\u003e \u003cp\u003eBetween January 2009 and June 2020, 705 ovarian cancer patients underwent germinal BRCA1/2 gene test. There were 308 patients enrolled in the study, including 108 BRCAmut patients and 200 BRCAwt patients. In the two groups, 36 patients (33.3%) and 59 patients (29.5%) received NAC, respectively, with no statistical difference (p\u0026thinsp;=\u0026thinsp;0.49). All patients received carboplatin, cisplatin, or nedaplatin based chemotherapy. The chemotherapy regimens and NAC cycles are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChemotherapy regimens of Patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBRCAmut\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBRCAwt\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimens of NAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarboplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCisplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNedaplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple platinum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCycle of NAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21 (35.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimens after surgery of NAC-IDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarboplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCisplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNedaplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple platinum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemotherapy regimens after surgery of PDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarboplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77 (54.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCisplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNedaplatin based\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple platinum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (20.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe characteristics of the patients were shown in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Among BRCAmut patients receiving NAC-IDS and PDS, the median ages at diagnosis were 53 years (range: 34\u0026ndash;71) and 52 years (range: 34\u0026ndash;79), respectively, with no significant difference. The pathological types of patients in both groups were mainly high-grade serous carcinoma (91.7% and 94.4%, respectively), and the proportion of the maximum volume of primary lesions at diagnosis was similar. The proportion of CA125 above 1000U/ml in patients with NAC was higher than patients with PDS (58.3% vs. 30.6%, p\u0026thinsp;=\u0026thinsp;0.002). After receiving NAC, the largest primary lesions in 75.0% of patients were reduced to less than 5cm; before chemotherapy, the proportion was only 13.9%. The operative time of patients in the two groups were similar, with a median of 155min (range: 80-370min) and 155min (range: 75-600min), respectively. However, the amount of blood loss in patients receiving NAC was significantly reduced than patients with PDS (300, range 100-1000ml vs. 400, rang 100-2000ml; p\u0026thinsp;=\u0026thinsp;0.044). Moreover, NAC significantly increased the proportion of R0 excisions (55.5% vs. 27.8%; p\u0026thinsp;=\u0026thinsp;0.004). For adverse reactions, the most common hematologic toxicities (CTCAE\u0026thinsp;\u0026ge;\u0026thinsp;3) were neutrophil count decreased and white blood cell count decreased, which were 22.2% and 19.4% in the neoadjuvant patients. The proportion of postoperative hematologic toxicities in the two groups was similar (p\u0026thinsp;=\u0026thinsp;0.644). In addition, it is worth noting that 52% of BRCAmut patients were treated with PARP inhibitors in the posterior lines of treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the BRCAmut Patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeoadjuvant Chemotherapy\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrimary Debulking Surgery (N\u0026thinsp;=\u0026thinsp;72)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u0026ndash;71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistologic type \u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (91.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerous not specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMucinous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear-cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIIB/IIIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVa/IVb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest primary tumor at diagnosed (cm)\u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5, \u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (52.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10, \u0026le;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest primary tumor before surgery (cm)\u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5, \u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10, \u0026le;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CA-125(U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual lesions (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (55.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (45.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (23.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of Operation(min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u0026ndash;370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemorrhage of Operation (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u0026ndash;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u0026ndash;2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse of NAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR/CR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD/PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of PARPi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (55.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic toxicity of NAC\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;3 CTCAE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic toxicity after surgery (\u0026ge;\u0026thinsp;3 CTCAE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (37.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the BRCAwt Patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeoadjuvant Chemotherapy\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrimary Debulking Surgery (N\u0026thinsp;=\u0026thinsp;141)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u0026ndash;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistologic type \u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh-grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (89.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow-grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerous not specified\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMucinous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClear-cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIIIB/IIIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (84.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVa/IVb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest tumor at diagnosed (cm)\u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (16.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5, \u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (45.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10, \u0026le;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLargest tumor before surgery (cm)\u0026mdash; no. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (61.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5, \u0026le;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10, \u0026le;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum CA-125(U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (30.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (53.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (34.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual lesions (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (42.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (28.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (27.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of Operation(min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u0026ndash;550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemorrhage of Operation (ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60-1500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u0026ndash;6000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse of NAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR/CR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD/PD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic toxicity of NAC\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;3 CTCAE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic toxicity after surgery (\u0026ge;\u0026thinsp;3 CTCAE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (18.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (29.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet decreased\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe median age at diagnosis was slightly higher in BRCAwt patients in both NAC-IDS and PDS group (56 and 53 years, respectively) compared to BRCAmut patients. The pathological type was dominated by high-grade serous carcinoma, and the proportion was similar between NAC-IDS and PDS groups. The proportion of FIGO stage III patients (84.7% vs. 92.9%, p\u0026thinsp;=\u0026thinsp;0.073) and surgical duration (median 145 vs. 155 min, p\u0026thinsp;=\u0026thinsp;0.758) were also similar between the two groups. There was no statistical difference in the proportion of the largest primary lesion. As in BRCAmut patients, the proportion of BRCAwt patients receiving NAC with ca125 level above 1000u/ml (44.1% vs. 34.0%; p\u0026thinsp;=\u0026thinsp;0.019) and the R0 resection rate (42.4% vs. 28.4%; p\u0026thinsp;=\u0026thinsp;0.034) were higher than those in PDS patients; however, the blood loss was significantly reduced (median 300 ml, range 60-1500ml vs. median 400ml, range 100-6000ml; p\u0026thinsp;=\u0026thinsp;0.019). The hematologic toxicity of NAC in BRCAwt patients was similar to that of BRCAmut, and there was no statistical difference in postoperative hematologic toxicity between NAC-IDS and PDS group (p\u0026thinsp;=\u0026thinsp;0.858). Finally, BRCAwt patients did not respond as significantly to NAC as BRCAmut; among the evaluable patients, the ratios of partial response (PR) were 50.0% (24/48) and 75.0% (21/28), respectively (p\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEffect of neoadjuvant chemotherapy on PFS and OS\u003c/h2\u003e \u003cp\u003eRegardless of the BRCA1/2 mutational status, there were no statistical differences in prognoses between patients in the NAC-IDS and PDS groups for PFS, (median: 15.4 vs. 14.9 months, HR\u0026thinsp;=\u0026thinsp;0.84; p\u0026thinsp;=\u0026thinsp;0.19) (Fig.\u0026nbsp;2A) or OS (median: 57.1 vs. 64.7 months, HR\u0026thinsp;=\u0026thinsp;1.11; p\u0026thinsp;=\u0026thinsp;0.56) (Fig.\u0026nbsp;3A). Further analysis found that the PFS of BRCAmut patients was significantly reduced after NAC (median, 15.0 vs. 19.0months, HR\u0026thinsp;=\u0026thinsp;0.59; p\u0026thinsp;=\u0026thinsp;0.03) (Fig.\u0026nbsp;2B); however, there was no statistical difference in OS (median, 75.1 vs. 68.5months, HR\u0026thinsp;=\u0026thinsp;0.90; p\u0026thinsp;=\u0026thinsp;0.72) (Fig.\u0026nbsp;3B). Whether BRCAwt patients received NAC had no significant effect on PFS (median, 13.5 vs. 14.6 months, HR\u0026thinsp;=\u0026thinsp;1.02; p\u0026thinsp;=\u0026thinsp;0.90) (Fig.\u0026nbsp;2C) and OS (median, 54.0 vs. 56.4 months, HR\u0026thinsp;=\u0026thinsp;1.23; p\u0026thinsp;=\u0026thinsp;0.34) (Fig.\u0026nbsp;3C).\u003c/p\u003e \u003cp\u003eCox regression multivariate analyses were performed, with PFS as the endpoint, and included the following variables: age at diagnosis, residual lesions, largest primary tumor size, FIGO stage, NAC-IDS or not, and CA-125 level. The strongest independent predictors of prolonged survival, in descending order PDS (p\u0026thinsp;=\u0026thinsp;0.003), were the absence of residual tumor after surgery (p\u0026thinsp;=\u0026thinsp;0.010) and FIGO III disease (p\u0026thinsp;=\u0026thinsp;0.011). The other variables did not significantly influence PFS (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate analysis of prognostic markers related to PFS in BRCAmut patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHR(95% Cl)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO (III / IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.397(0.194\u0026ndash;0.811)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAC-IDS (No / Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.393(0.211\u0026ndash;0.732)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidual Lesions(R0 / R1\u0026thinsp;+\u0026thinsp;R2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.490(0.285\u0026ndash;0.840)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA-125 (\u0026le;\u0026thinsp;1000 / \u0026gt;1000 U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.794(0.464\u0026ndash;1.359)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(\u0026le;50 / \u0026gt;50 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.887 (0.522\u0026ndash;1.507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaximum of Lesions (\u0026le;\u0026thinsp;10 / \u0026gt;10 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.636(0.345\u0026ndash;1.171)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this retrospective study, we found that without considering the BRCA1/2 mutation status, both PFS and OS after neoadjuvant chemotherapy followed by interval debulking surgery were similar to survivals with primary surgery followed by chemotherapy, which was consistent with the conclusions of previous randomized controlled trials[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In BRCAmut patients, NAC-IDS significantly shortened PFS, however, it had no effect on OS. For BRCAwt patients, NAC did not significantly affect the prognosis. To our knowledge, this is the first retrospective study to date to discuss the effect of NAC on prognosis based on the BRCA mutational status.\u003c/p\u003e \u003cp\u003eThe proportion of patients with BRCA1/2 mutations was 35.1%, which is much higher than that previously reported in the literature[\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This could be related to the fact that all patients included in the study were at an advanced stage. Both BRCA1 and BRCA2 are tumor suppressor genes, and their functional proteins play an important role in DNA homologous recombinant double-stranded break repair. In the absence of functional BRCA1/2 gene, tumor cells are more aggressive and therefore more prone to distant metastasis, leading to an increased proportion of patients with FIGO III and IV stage[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. According to previous reports, the highest proportion of BRCA1/2 mutation in Chinese ovarian cancer patients was 28.5%. However, if stage III and IV patients were separately counted, the proportion of patients with BRCA1/2 mutation was significantly increased in these studies[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary evaluation criteria for the initial treatment of advanced ovarian cancer patients is whether satisfactory cytoreductive surgery can be achieved in PDS, especially R0 resection, which could significantly prolong survival[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. At present, clinical practice guidelines and expert consensus suggest that NAC is recommended for FIGO stage III to IV patients with poor physical status and unable to tolerate surgery, and for patients in whom it is difficult to achieve satisfactory tumor cytoreductive surgery (R0 and R1)[\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Several studies have confirmed that the serum CA-125 level was an important predictor of surgical outcome, defined as successful cytoreductive surgery with a residual tumor\u0026thinsp;\u0026le;\u0026thinsp;1 cm, and is a significant factor in decision-making regarding the proper selection for PDS or NAC[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In our study, the largest primary lesion at diagnosis was similar in both the NAC and PDS groups regardless of BRCA mutation, but the CA-125 levels in patients receiving NAC were significantly higher than those in the PDS group, which is one of the important reasons for choosing NAC. In addition, NAC can significantly increase the proportion of R0 resection and reduce the amount of bleeding during surgery, consistent with the conclusions of previous reports[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough R0 resection rates were significantly improved in both BRCAmut and BRCAwt patients receiving NAC, the OS did not improve, nor did PFS in BRCAwt patients. In contrast, in BRCAmut patients, NAC significantly shortened PFS; further multivariate analysis found that NAC-IDS, FIGO IV stage, and R1/R2 resection were risk factors for poor PFS. Compared with BRCAwt patients, BRCAmut patients previously showed a significantly increased peritoneal tumor load[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], were associated with nodular peritoneal disease pattern[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and showed increased sensitivity to NAC[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In our study, the proportion of BRCAmut patients who achieved partial response after neoadjuvant chemotherapy was 75.0%, which was significantly higher than that of BRCAwt patients (50%). The above reasons could cause more peritoneal lesions to become invisible after NAC and, thus, cannot be completely resected; therefore, R0 resection may not be truly achieved; instead, the complete response (CR) status was achieved through chemotherapy, which may be the main reason for reduced PFS in BRCAmut patients.\u003c/p\u003e \u003cp\u003eBRCA1/2 genes are tumor suppressors, that play an important role in DNA damage repair and normal cell growth. BRCA1/2 mutations can inhibit the repair of DNA damage, resulting in homologous recombination deficiency, which eventually lead to carcinogenesis[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In BRCA1/2 mutated tumor cells, DNA double-stranded repair function is lost; since PARP inhibitors can block single-stranded DNA repair, this results in a \"synthetic lethal\" effect that leads to the death of tumor cells[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, PARP inhibitors have excellent maintenance treatment effects in BRCAmut patients, which can significantly prolong the PFS and OS[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In the SOLO-2 clinical trial of olaparib[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], maintenance therapy with olaparib in BRCAmut platinum-sensitive relapse patients extended the relapse time by 24.7 months and reduced the risk of recurrence or death by 70%. In addition, the objective response rate in BRCAmut patients with platinum-sensitive relapses above three lines was about 70% when treated with PARP inhibitors[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The evaluation of PFS in our study, although excluding patients with PARP inhibitors for maintenance therapy, there were a large number of patients treated with PARP inhibitors in the posterior line of treatment. This is probably the main reason for the subsequent overall survival consistency.\u003c/p\u003e \u003cp\u003eThis retrospective study had several limitations. First, several studies have suggested that surgery is appropriate after three cycles of NAC[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Patients with 1\u0026ndash;3 cycles were included in our study; however, patients with one cycle of chemotherapy, were not suitable if PR was not achieved, which may affect the prognosis to some extent. In addition, we did not collect details of patients using PARP inhibitors in the posterior line; therefor, no further analysis of OS was performed to exclude the effect of PARP inhibitors.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, for advanced-stage ovarian cancer patients treated with NAC followed by IDS, PFS and OS were not significantly affected in BRCAwt patients. In BRCAmut patients, NAC-IDS resulted in a shortened PFS, but had no further effect on OS. Additional randomized controlled trials will be necessary to elucidate the effect of BRCA1/2 mutation on prognoses of advanced-stage ovarian cancer patients.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNAC: Neoadjuvant chemotherapy; IDS: Interval debulking surgery; PDS: Primary debulking surgery; BRCA: Breast Cancer Susceptibility Genes; FIGO: International Federation of Gynecology and Obstetrics; PFS: Progression-free survival; OS: Overall survival; PAPR: Poly (ADP‐ribose) polymerase; RECIST: Response evaluation criteria in solid tumors; NGS: Next generation sequence; HR: Hazard ratios; CI: Confidence intervals; CA125: cancer antigen 125; CTCAE: Common Terminology Criteria for Adverse Events.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of Qilu Hospital of Shandong University, and informed consents were obtained from all patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Department of Science Technology of Jinan city (No. 201705051).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMengdi Fu: Conceptualization, investigation, methodology, project administration, and writing‐original draft. Chengjuan Jin: Data curation, formal analysis, and software. Jingying Chen, Shuai Feng, Lekai Nie, Xia Wang, and Yang Zhang: Data curation. Jin Peng: Funding acquisition, investigation and methodology. Hualei Bu and Beihua Kong: Formal analysis, methodology, supervision, validation, review, and editing. All authors have reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSiegel RL, Miller KD, Fuchs HE, Jemal A. Cancer Statistics. 2021. CA Cancer J Clin. 2021;71:7\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaik ES, Lee YY, Lee EJ, Choi CH, Kim TJ, Lee JW, et al. Survival analysis of revised 2013 FIGO staging classification of epithelial ovarian cancer and comparison with previous FIGO staging classification. 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Eur J Cancer. 2016;59:22\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBu H, Chen J, Li Q, Hou J, Wei Y, Yang X, et al. BRCA mutation frequency and clinical features of ovarian cancer patients: A report from a Chinese study group. J Obstet Gynaecol Res. 2019;45:2267\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu X, Wu L, Kong B, Liu J, Yin R, Wen H, et al. The First Nationwide Multicenter Prevalence Study of Germline BRCA1 and BRCA2 Mutations in Chinese Ovarian Cancer Patients. Int J Gynecol Cancer. 2017;27:1650\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi T, Wang P, Xie C, Yin S, Shi D, Wei C, et al. BRCA1 and BRCA2 mutations in ovarian cancer patients from China: ethnic-related mutations in BRCA1 associated with an increased risk of ovarian cancer. Int J Cancer. 2017;140:2051\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolton KL, Chenevix-Trench G, Goh C, Sadetzki S, Ramus SJ, Karlan BY, et al. Association between BRCA1 and BRCA2 mutations and survival in women with invasive epithelial ovarian cancer. JAMA. 2012;307:382\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColombo N, Sessa C, du Bois A, Ledermann J, McCluggage WG, McNeish I, et al. ESMO-ESGO consensus conference recommendations on ovarian cancer: pathology and molecular biology, early and advanced stages, borderline tumours and recurrent diseasedagger. Ann Oncol. 2019;30:672\u0026ndash;705.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWright AA, Bohlke K, Armstrong DK, Bookman MA, Cliby WA, Coleman RL, et al. Neoadjuvant Chemotherapy for Newly Diagnosed, Advanced Ovarian Cancer: Society of Gynecologic Oncology and American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol. 2016;34:3460\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuh DH, Chang SJ, Song T, Lee S, Kang WD, Lee SJ, et al. Practice guidelines for management of ovarian cancer in Korea: a Korean Society of Gynecologic Oncology Consensus Statement. J Gynecol Oncol. 2018;29:e56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArab M, Jamdar F, Sadat Hosseini M, Ghodssi- Ghasemabadi R, Farzaneh F, Ashrafganjoei T. Model for Prediction of Optimal Debulking of Epithelial Ovarian Cancer. Asian Pac J Cancer Prev. 2018;19:1319\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaygili U, Guclu S, Uslu T, Erten O, Demir N, Onvural A. Can serum CA-125 levels predict the optimal primary cytoreduction in patients with advanced ovarian carcinoma? Gynecol Oncol. 2002;86:57\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGemer O, Lurian M, Gdalevich M, Kapustian V, Piura E, Schneider D, et al. A multicenter study of CA 125 level as a predictor of non-optimal primary cytoreduction of advanced epithelial ovarian cancer. Eur J Surg Oncol. 2005;31:1006\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrillo M, Marchetti C, De Leo R, Musella A, Capoluongo E, Paris I, et al. BRCA mutational status, initial disease presentation, and clinical outcome in high-grade serous advanced ovarian cancer: a multicenter study. Am J Obstet Gynecol. 2017;217:334. e1- e9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNougaret S, Lakhman Y, Gonen M, Goldman DA, Micco M, D'Anastasi M, et al. High-Grade Serous Ovarian Cancer: Associations between BRCA Mutation Status, CT Imaging Phenotypes, and Clinical Outcomes. Radiology. 2017;285:472\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGorodnova TV, Sokolenko AP, Ivantsov AO, Iyevleva AG, Suspitsin EN, Aleksakhina SN, et al. High response rates to neoadjuvant platinum-based therapy in ovarian cancer patients carrying germ-line BRCA mutation. Cancer Lett. 2015;369:363\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonstantinopoulos PA, Ceccaldi R, Shapiro GI, D'Andrea AD. Homologous Recombination Deficiency: Exploiting the Fundamental Vulnerability of Ovarian Cancer. Cancer Discov. 2015;5:1137\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore K, Colombo N, Scambia G, Kim BG, Oaknin A, Friedlander M, et al. Maintenance Olaparib in Patients with Newly Diagnosed Advanced Ovarian Cancer. N Engl J Med. 2018;379:2495\u0026ndash;505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEssel KG, Moore KN. Niraparib for the treatment of ovarian cancer. Expert Rev Anticancer Ther. 2018;18:727\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePujade-Lauraine E, Ledermann JA, Selle F, Gebski V, Penson RT, Oza AM, et al. Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18:1274\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Neoadjuvant chemotherapy, primary debulking surgery, BRCA, prognosis","lastPublishedDoi":"10.21203/rs.3.rs-786505/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-786505/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWhether neoadjuvant chemotherapy (NAC) followed by interval debulking surgery (IDS) against primary debulking surgery (PDS) has a differential effect on prognosis due to Breast Cancer Susceptibility Genes (BRCA)1/2 mutations has not been confirmed by current studies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAll patients included in this retrospective study were admitted to Qilu Hospital of Shandong University between January 2009 and June 2020, and germline BRCA1/2 mutation were tested. Patients in stage IIIB, IIIC, and IV, re-staged by International Federation of Gynecology and Obstetrics (FIGO) 2014, were selected for analysis. All patients with NAC received 1\u0026ndash;3 cycles of platinum-containing (carboplatin, cisplatin, or nedaplatin) chemotherapy. Patients who received maintenance therapy after chemotherapy were not eligible for this study. All relevant medical records were collected.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 308 patients were enrolled in the study, including 108 patients with BRCA1/2 mutations (BRCAmut), and 200 patients with BRCA1/2 wild-type (BRCAwt). In the two groups, 36 BRCAmut patients (33.3%) and 59 BRCAwt patients (29.5%) received neoadjuvant chemotherapy. The progression-free survival (PFS) of BRCAmut patients was significantly reduced after NAC (median: 15.0 vs. 19.0 months, HR\u0026thinsp;=\u0026thinsp;0.59; p\u0026thinsp;=\u0026thinsp;0.03); however, there was no statistical difference in overall survival (OS) (median: 75.1 vs. 68.5 months, HR\u0026thinsp;=\u0026thinsp;0.90; p\u0026thinsp;=\u0026thinsp;0.72). Whether BRCAwt patients received NAC had no significant effect on PFS (median: 13.5 vs. 14.6 months, HR\u0026thinsp;=\u0026thinsp;1.02; p\u0026thinsp;=\u0026thinsp;0.90) or OS (median: 54.0 vs. 56.4 months, HR\u0026thinsp;=\u0026thinsp;1.23; p\u0026thinsp;=\u0026thinsp;0.34). Multivariate analyses showed that the independent predictors of prolonged survival were PDS (p\u0026thinsp;=\u0026thinsp;0.003), the absence of residual tumor after surgery (p\u0026thinsp;=\u0026thinsp;0.010), and FIGO III stage (p\u0026thinsp;=\u0026thinsp;0.011).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFor advanced-stage ovarian cancer patients treated with NAC followed by IDS, PFS and OS were not significantly affected in BRCAwt patients. In BRCAmut patients, NAC-IDS resulted in a shortened PFS, but had no further effect on overall survival.\u003c/p\u003e","manuscriptTitle":"Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-10 14:52:38","doi":"10.21203/rs.3.rs-786505/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d56a53d-884d-443e-ab94-bd051ae712d8","owner":[],"postedDate":"August 10th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":6336994,"name":"Sexual \u0026 Reproductive Medicine"},{"id":6336995,"name":"Cancer Biology"}],"tags":[],"updatedAt":"2022-01-06T06:31:50+00:00","versionOfRecord":{"articleIdentity":"rs-786505","link":"https://doi.org/10.3389/fonc.2021.810099","journal":{"identity":"frontiers-in-oncology","isVorOnly":true,"title":"Frontiers in Oncology"},"publishedOn":"2022-01-06 06:31:50","publishedOnDateReadable":"January 6th, 2022"},"versionCreatedAt":"2021-08-10 14:52:38","video":"","vorDoi":"10.3389/fonc.2021.810099","vorDoiUrl":"https://doi.org/10.3389/fonc.2021.810099","workflowStages":[]},"version":"v1","identity":"rs-786505","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-786505","identity":"rs-786505","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}