Safety assessments and clinical features of PARP inhibitors from real-world data of Japanese patients with ovarian cancer

Safety assessments and clinical features of PARP inhibitors from real-world data of Japanese patients with ovarian cancer | 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 Article Safety assessments and clinical features of PARP inhibitors from real-world data of Japanese patients with ovarian cancer Ryosuke Uekusa, Akira Yokoi, Eri Watanabe, Kosuke Yoshida, Masato Yoshihara, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3129590/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Poly (ADP-ribose) polymerase (PARP) inhibitors, such as olaparib and niraparib, have been increasingly used in ovarian cancer treatment. However, the real-world safety data of these drugs in Japanese patients and the predictability of treatment interruptions are limited. Methods This retrospective study included 181 patients with ovarian cancer who received olaparib or niraparib at two independent hospitals in Japan between May 2018 and December 2022. Clinical information and blood sampling data were collected. Patient characteristics, treatment history, and hematological data trends were compared, and the predictability of treatment interruptions based on blood sampling data was examined. Results Regarding patient backgrounds, the olaparib group had higher proportions of patients with serous carcinoma, BRCA positivity, homologous recombination deficiency, and those receiving maintenance therapy after recurrence treatment than the niraparib group. Regarding toxicity properties, the most common reasons for discontinuation in the olaparib group were anemia, fatigue, and nausea, while discontinuation was primarily due to thrombocytopenia in the niraparib group. Thrombocytopenia caused by niraparib treatment occurred earlier than anemia caused by olaparib treatment. Patients with a low body mass index or who had undergone several previous treatment regimens were more likely to discontinue treatment due to adverse effects within the first 3 months. Although we analyzed blood collection data, predicting treatment interruptions due to blood toxicity using blood data was challenging. Conclusions In this study, we revealed the characteristics of patients and the timing of interruptions for each drug, highlighting the importance of carefully managing adverse effects, particularly during the early treatment stages. Ovarian cancer PARP inhibitors olaparib niraparib adverse effects Figures Figure 1 Figure 2 Introduction Ovarian cancer is the third most common gynecologic malignancy and was the second leading cause of death from gynecologic cancer worldwide in 2020[ 1 ]. Epithelial ovarian cancer constitutes most ovarian malignancies, with most cases diagnosed at an advanced stage. The 5-year survival rate for ovarian cancer is approximately 30%. Despite achieving an approximately 80% response rate with standard treatment of optimal debulking surgery and platinum-based chemotherapy, most patients experience recurrence and disease progression within 2 y, leading to multiple recurrences and the development of platinum-resistant ovarian cancer[ 2 ][ 3 ]. Therefore, extending the progression-free period and improving the 5-year survival rate are urgent challenges. Poly (ADP-ribose) polymerase (PARP) inhibitors have emerged as a significant breakthrough in managing advanced ovarian cancer in recent years[ 4 ]. PARP is an enzyme crucial for repairing single-strand DNA breaks. PARP inhibitors are a class of drugs that block PARP enzyme activity, causing the accumulation of single-strand breaks, which eventually turn into double-strand breaks (DSBs). DSBs can be repaired by a homologous recombination repair (HRR) pathway. However, in cancer cells with BRCA mutations or homologous recombination deficiency (HRD), the HRR pathway is already impaired. Thus, when PARP inhibitors are used to treat these cells, they further compromise DNA repair mechanisms by blocking the repair of single-strand breaks. This creates a state of synthetic lethality, as the combined effect of the impaired HRR pathway and PARP inhibition induces excessive DNA damage, causing cancer cell death [ 5 ]. In Japan, olaparib has received approval for various maintenance treatments, including platinum-sensitive relapsed ovarian cancer in 2018[ 6 ] [ 7 ], BRCA mutations following remission of first-line platinum chemotherapy in 2019[ 8 ], and HRD in combination with bevacizumab after remission of first-line platinum chemotherapy in 2020[ 9 ]. Conversely, niraparib was approved for maintenance treatment of platinum-sensitive relapsed ovarian cancer in 2020[ 10 ], maintenance treatment following remission of first-line platinum chemotherapy in 2020[ 11 ], and monotherapy treatment of HRD and platinum-sensitive relapsed ovarian cancer after third or more chemotherapy sessions in 2020[ 12 ] . Since eligibility criteria restrict patient enrollment in clinical trials and the adverse effects observed may vary due to racial differences, clinical trial results do not necessarily correspond to real-world practice. Thus, there is growing interest in using real-world data to answer clinical questions unanswerable through clinical trial data[ 13 ] [ 14 ]. Furthermore, accumulating real-world data may reveal findings unavailable in clinical trials or even overturn clinical trial data. Since maintenance therapy follows an initial treatment, accumulating the clinical data takes time. Olaparib and niraparib have been used for 5 and 2 y, respectively, in Japan. Therefore, we examined the real-world data on the safety of both drugs. Additionally, we assessed whether interruptions could be predicted and whether certain trends existed among patients who interrupted the drugs. Patients and Methods The records of 181 patients with ovarian cancer who received olaparib and/or niraparib treatment at Nagoya University Hospital (Nagoya, Japan) and Aichi Cancer Center Hospital (Nagoya, Japan) from May 2018 to December 2022 were retrospectively reviewed. Both the olaparib and niraparib groups included patients undergoing maintenance treatment for advanced epithelial ovarian, fallopian tube, or primary peritoneal cancer after first-line platinum-based chemotherapy and recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer after platinum-based chemotherapy. We investigated the patients’ clinical information, including age, body mass index (BMI), smoking and drinking habits, histological type, BRCA and HRD status, previous chemotherapy regimens, adverse effects, and blood sampling data, at several points. This study was approved by the ethics committee of each institute (Approval No. 2013-0078). Statistical analyses were performed using GraphPad Prism 9, with the Mann–Whitney U test used for comparisons between both groups. p < 0.05 was considered statistically significant. Results Patient characteristics The olaparib and niraparib groups comprised 131 and 50 patients, respectively (Table 1 ). The median age was 59 (30–80) in the olaparib group and 50 (23–80) in the niraparib group, while the median BMI was 21.2 (14.2–32.8) in the olaparib group and 21.9 (14.3–30.4) in the niraparib group. There were no differences in smoking habits or diabetes between both groups, but alcohol consumption was higher in the niraparib group ( p = 0.01). Table 1 Patient characteristics Olaparib (N = 131) Niraparib (N = 50) p value Age 59 (30–80) 59 (23–80) 0.57 BMI 21.2 (14.2–32.8) 21.9 (14.3–30.4) 0.54 Smoking 14 (10.7%) 8 (16.0%) 0.59 Drinking 9 (6.9%) 10 (20.0%) 0.01 DM 9 (6.9%) 5 (10.0%) 0.53 Histologic subtype Serous 115 (87.8%) 32 (64.0%) < 0.01 Endometrioid 9 (6.9%) 6 (12.0%) Clear 5 (3.8%) 5 (10.0%) Carcinosarcoma 0 (0.0%) 1 (2.0%) Unknown 2(1.5%) 6 (12.0%) BRCA status Positive 26 (19.8%) 2 (4.0%) 0.01 Negative 36 (27.5%) 26 (52. 0%) Unknown 69 (52.7%) 22 (44. 0%) HRD Positive 19 (14.5%) 4 (8.0%) 0.32 Negative 2 (1.5%) 12 (24.0%) Unknown 110 (83.9%) 33 (66.0%) BMI, body mass index; DM, diabetes mellitus; HRD, homologous recombination deficiency The proportion of serous carcinoma was significantly higher in the olaparib group (115/131, 87.8%) compared to the niraparib group (32/50, 64.0%) ( p < 0.01). The proportion of BRCA -positive patients was 26/131 (19.8%) in the olaparib group and 2/50 (4.0%) in the niraparib group ( p = 0.05), while that of HRD-positive patients was 19/131 (14.5%) in the olaparib group and 4/50 (8.0%) in the niraparib group ( p = 0.32). In addition, the BRCA status was unknown for 69/131 (52.7%) patients in the olaparib group and 22/50 (44.0%) patients in the niraparib group. The HRD status was unknown for 110/131 (83.9%) patients in the olaparib group and 33/50 (66.0%) patients in the niraparib group. Treatment history The patients’ treatment history is shown in Table 2 . The median observation period was 697 (68–1699) d in the olaparib group and 423 (66–726) d in the niraparib group. The median treatment duration was 190 (14–1667) d in the olaparib group and 203 (5–726) d in the niraparib group. Treatment was discontinued due to adverse effects in 22/131 (16.8%) patients in the olaparib group and 6/50 (12.0%) patients in the niraparib group. The response to the most recent treatment was similar in both groups. Table 2 Treatment history Olaparib (N = 131) Niraparib (N = 50) p value Observation days (days) 697 (68–1699) 423 (66–726) Duration to the treatment (days) 190 (14–1667) 203 (5–726) Reason for termination PD 63 (48.1%) 29 (58.0%) Adverse effect 22 (16.8%) 6 (12.0%) Others 2 (0.0%) 1 (2.0%) Number of previous chemotherapy regimens 1 ~ 4 114 (87.0%) 49 (98.0%) 5 ~ 9 13 (9.9%) 1 (2.0%) 10~ 4 (3.1%) 0 (0.0%) Response to most recent treatment CR 62 (47.3%) 27 (54.0%) 0.51 PR 69 (52.7%) 23 (46.0%) Maintenance for first-line chemotherapy 31 (23.7%) 28 (56.0%) < 0.01 Treatment with Bev 18 (13.7%) - No surgery 5 (3.8%) 10 (20.0%) < 0.01 Interruption 68 (51.9%) 32 (64.0%) 0.87 Reason for interruption Anemia 33 (48.5%) 8 (25.0%) Neutropenia 17 (25.0%) 5 (15.6%) Thrombocytopenia 6 (8.8%) 16 (50.0%) Fatigue 14 (20.6%) 2 (6.3%) Nausea 11 (16.2%) 0 (0.0%) Others 8 (11.8%) 7 (21.9%) CR, complete response; PR, partial response; PD, progressive disease Furthermore, 31/131 (23.7%) in the olaparib group and 28/50 (56.0%) in the niraparib group received maintenance therapy following first-line chemotherapy. Maintenance therapy in combination with bevacizumab was administered to 18/131 (13.7%) patients in the olaparib group. Additionally, 5/131 (3.8%) patients in the olaparib group and 10/50 (20.0%) patients in the niraparib group were transferred to maintenance therapy without surgery ( p < 0.01). Treatment was interrupted in 68/131 (51.9%) patients in the olaparib group and 32/50 (64.0%) patients in the niraparib group (p = 0.87). The most common reason for treatment interruption based on blood data was anemia in 33/68 (48.5%) patients in the olaparib group and thrombocytopenia in 16/32 (50.0%) patients in the niraparib group. In the olaparib group, 20/68 (55.6%) patients interrupted treatment due to fatigue and/or nausea. The characteristics of cases where treatment was discontinued due to adverse effects in the early treatment stage are shown in Table 3 . A total of 13/131 (9.9%) patients in the olaparib group and 5/50 (10.0%) patients in the niraparib group discontinued treatment due to adverse effects within the first 3 months of treatment. The median treatment duration was 43 (14–77) d in the olaparib group and 27 (5–28) d in the niraparib group. The median BMI was 19.9 (14.2–26.5) in the olaparib group and 20.5 (14.3–24.9) in the niraparib group, indicating that both groups had a higher proportion of thin patients compared to the overall population. In both groups, most patients received maintenance therapy after recurrence. The most common reason for early treatment discontinuation was fatigue or vomiting in 8/13 (61.5%) patients in the olaparib group and thrombocytopenia in 3/5 (60.0%) patients in the niraparib group. Table 3 The characteristics of patients who discontinued treatment due to adverse effects within the first 3 months of treatment Olaparib (N = 131) Niraparib (N = 50) Discontinued cases 13 (9.9%) 5 (10.0%) Duration to the treatment(days) 56 (14–154) 27 (5–28) BMI 20.1 (14.2–29.5) 20.5 (14.3–24.9) Smoking 1 (7.7%) 1 (20.0%) Drinking 0 (0.0%) 0 (0.0%) DM 1 (7.7%) 0 (0.0%) Number of previous chemotherapy regimens 2 (1–6) 2 (1–3) Response to most recent treatment CR 9 (69.2%) 1 (20.0%) PR 4 (30.8%) 4 (80.0%) Maintenance for first-line chemotherapy 3 (23.1%) 1 (20.0%) Reason for termination Anemia 2 (15.4%) 0 (0.0%) Neutropenia 1 (7.7%) 0 (0.0%) Thrombocytopenia 0 (0.0%) 3 (60.0%) Fatigue, Vomiting 8 (61.5%) 1 (20.0%) Dysgeusia 1 (7.7%) 1 (20.0%) Interstitial pneumonia 1 (7.7%) 0 (0.0%) BMI, body mass index; DM, diabetes mellitus; CR, complete response; PR, partial response Hematological data trends The trends of blood hemoglobin and platelet levels, which were the most common causes of treatment interruption based on blood data, in the olaparib and niraparib groups, respectively, are shown in Fig. 1 a. In the olaparib group, there were 30 cases of initial treatment interruption due to anemia after the start of treatment. Among these, 22/30 (73.3%) were interrupted within 4–12 weeks of treatment. Conversely, there were 16 cases of initial treatment interruption due to thrombocytopenia in the niraparib group (Fig. 1 b). Among these, 15/16 (93.8%) were interrupted within 8 weeks of treatment. Interruptions due to thrombocytopenia in the niraparib group tended to occur earlier than interruptions due to anemia in the olaparib group. As described above, the timing of interruptions showed certain trends and characteristics for each drug. Prediction of interruption Predicting adverse effects in patients would enhance treatment management and ensure safe administration of the drug, leading to successful completion of the treatment. We hypothesized that the degree of adverse effects during chemotherapy might correlate with that during maintenance therapy using consecutive PARP inhibitors. Therefore, to predict treatment interruption due to hematological adverse effcts, blood collection data before treatment and after chemotherapy were investigated. Specifically, we compared the blood collection data at the initial visit and at the start of olaparib/niraparib treatment and the rate of change between the groups with and without interruption. The results for interruption due to anemia in the olaparib group are shown in Fig. 2 a. No significant differences existed between both groups, and predicting interruption due to anemia from the blood data at the initial visit or the start of treatment was challenging. The results for interruption due to thrombocytopenia in the niraparib group are shown in Fig. 2 b. No significant differences existed between both groups, and predicting interruption due to thrombocytopenia from the blood data at the initial visit or the start of treatment was challenging. Both olaparib-induced interruption due to anemia and niraparib-induced interruption due to thrombocytopenia were difficult to predict from the blood data. Discussion Due to the high recurrence rate and low survival rate of ovarian cancer, as well as the limited availability of drugs other than chemotherapy in the past, the emergence of PARP inhibitors has brought hope for ovarian cancer treatment[ 15 ]. We aimed to explore the real-world data of olaparib and niraparib in Japan, as both agents target the same pathways but are used differently. Olaparib is primarily used as a single agent in maintenance therapy after first-line chemotherapy for BRCA -positive patients, based on the SOLO-1 study[ 8 ], and in combination with bevacizumab for HRD patients, based on the PAOLA-1 study[ 9 ]. Conversely, niraparib can be used regardless of biomarkers, based on the PRIMA study[ 11 ]. BRCA mutations and HRD are frequently observed in high-grade serous ovarian carcinoma[ 16 ], suggesting that the niraparib group may have had fewer patients with serous carcinoma, BRCA -positive status, and HRD. The complete response rate after the most recent platinum-based chemotherapy was 47.3% in the olaparib group and 54.0% in the niraparib group. When limited to patients receiving maintenance therapy after first-line chemotherapy, the rate was 93.5% in the olaparib group and 60.7% in the niraparib group, similar to prior studies[ 8 ] [ 9 ] [ 11 ]. In this study, there were differences in adverse effects between the olaparib group and the niraparib group. Despite sharing the same pharmacological mechanism, the toxicity profile is different for both agents[ 17 ] [ 18 ]. The differences in adverse effects of these agents could be attributed to dosage schedule, half-life, drug interactions, and metabolism[ 19 ]. In this study, Grade 3 or 4 adverse reactions in the olaparib group included anemia (25.2%), neutropenia (14.5%), thrombocytopenia (3.8%), and fatigue/nausea (15.3%), occurring more frequently than in previous studies [ 6 ] [ 7 ] [ 8 ] [ 9 ]. This discrepancy might be because the Japanese have a lower BMI than Westerners. Conversely, Grade 3 or 4 adverse reactions in the niraparib group comprised anemia (14.0%), neutropenia (10.0%), thrombocytopenia (32.0%), and fatigue/nausea (6.0%), respectively, with these results either being the same or less frequent than in previous studies[ 10 ] [ 11 ] [ 20 ]. This may be because the starting dose for niraparib was individualized based on body weight and platelet count. Previous studies started with a fixed dose of 300 mg, and the NOVA trial results led to the individualization of the initial dose according to body weight and platelet count. Moreover, recently published data from the NORA trial confirmed that dose individualization is associated with improved hematologic toxicity[ 21 ]. Thrombocytopenia is a peculiar toxicity observed in niraparib treatment, and we showed that niraparib-induced thrombocytopenia occurs earlier than olaparib-induced anemia. Furthermore, there were three cases where platelet levels did not recover after treatment interruption, leading to the discontinuation of the drug. This finding suggests that niraparib-induced thrombocytopenia may be more robust than olaparib-induced anemia. Among patients who discontinued treatment due to adverse effects, 59% in the olaparib group and 100% in the niraparib group discontinued within the first 3 months of treatment. It was considered that thin patients with several previous regimens should be managed with particular attention to adverse effects early in the treatment. Furthermore, careful long-term management of adverse effects is crucial, especially when treated with olaparib. While there have been many reports on the adverse effects of PARP inhibitor therapy[ 22 ] [ 23 ], no reports describing their predictability exist. This is the first study on the predictability of interruptions in PARP inhibitor therapy using blood collection data. However, the blood toxicity of both agents was difficult to predict using blood collection data. Generally, hematological adverse events associated with PARP inhibitors are frequent but transient, occurring during the first months of therapy, and are often resolved with dose reduction. We also observed hematological adverse events in the later treatment stages, especially in the olaparib group, and rare complications such as myelodysplastic syndrome and acute myeloid leukemia[ 24 ]. Thus, regular blood tests should be conducted even after the initial months of treatment. In conclusion, we examined the real-world data on the safety of olaparib and niraparib, as well as the predictability of intake interruption based on blood sampling data. Patient backgrounds and toxicity profiles differed between the olaparib and niraparib groups. However, predicting the blood toxicity of both agents using blood collection data was challenging. This study revealed the characteristics of the patients and the timing of interruption for each drug and highlighted the importance of carefully managing adverse effects, particularly during the early treatment stages. Declarations Acknowledgements We express the highest appreciation to the entire staff of the Department of Obstetrics and Gynecology, Nagoya University Graduate School of Medicine, and Department of Gynecology, Aichi Cancer Center. This work was supported by JSPS KAKENHI Grant Number 21H03075 and the Princess Takamatsu Cancer Research Fund (No. 20-25237), Moreover, this study was also supported by Program for Tokai Pathway to Global Excellence (T-GEx) FY2021 and for Promoting the Enhancement of Research Universities as young researcher units for the advancement of new and undeveloped fields at Nagoya University. Furthermore, we thank Enago (https://www.enago.jp/) for English language editing of this manuscript. Data availability statements All data generated or analyzed during this study are included in this published article. Contributions All authors contributed to the study conception and design. Data collection and analysis were performed by R.U., E.W., and A.Y. The first draft of the manuscript was written by R.U. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. 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Lancet Oncol 20 (1):e15-e28. doi:10.1016/S1470-2045(18)30786-1 Stemmer A, Shafran I, Stemmer SM, Tsoref D (2020) Comparison of Poly (ADP-ribose) Polymerase Inhibitors (PARPis) as Maintenance Therapy for Platinum-Sensitive Ovarian Cancer: Systematic Review and Network Meta-Analysis. Cancers (Basel) 12 (10). doi:10.3390/cancers12103026 Morice PM, Leary A, Dolladille C, Chretien B, Poulain L, Gonzalez-Martin A, Moore K, O'Reilly EM, Ray-Coquard I, Alexandre J (2021) Myelodysplastic syndrome and acute myeloid leukaemia in patients treated with PARP inhibitors: a safety meta-analysis of randomised controlled trials and a retrospective study of the WHO pharmacovigilance database. Lancet Haematol 8 (2):e122-e134. doi:10.1016/S2352-3026(20)30360-4 Cite Share Download PDF Status: Posted 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-3129590","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":216745987,"identity":"2ed19aab-fb69-43da-87d1-163dd50292ae","order_by":0,"name":"Ryosuke Uekusa","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ryosuke","middleName":"","lastName":"Uekusa","suffix":""},{"id":216745988,"identity":"c0885d69-1e1e-4273-b5e7-550d83095504","order_by":1,"name":"Akira Yokoi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYHACZgYGAxsgnYAhjFdLGslaGA5jasEJ+GckHzb4UHA+mp89ge3Bj182if0NPAYMP2oY2M1xaJG4kZacOMPgdu7Mngfshr19aYkzDvAYMPYcY2C2bMCh50aO8WEeoJYNNxLYJHh7Dic23H9jwMDbwMBscAC7DnmIlnO5+4FaJP8CtcwH2fIXjxYDoJZkHoMDuRskEtikeX4cTtwA1MKMzxbDM8+SDWcYJOfOOPOwTVq2Ic144wG2gsMyxyRw+kXuePJhiQ9/7HL725OPSb75YyM77wDzxodvamyScYUYg0ACjMXYwMDYxuAIMhvoJIlkA1xa+FFc/IfBHsa0w6llFIyCUTAKRhoAAMvlXakBUa+ZAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0789-5102","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Yokoi","suffix":""},{"id":216745989,"identity":"24edc69f-d910-4424-8a61-3d501f9d9241","order_by":2,"name":"Eri Watanabe","email":"","orcid":"","institution":"Aichi Cancer Center Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eri","middleName":"","lastName":"Watanabe","suffix":""},{"id":216745990,"identity":"a1b4efed-61b9-4f49-a79b-133ead4347db","order_by":3,"name":"Kosuke Yoshida","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kosuke","middleName":"","lastName":"Yoshida","suffix":""},{"id":216745991,"identity":"48f177cc-3e3a-4e13-a19b-e2db9a373d76","order_by":4,"name":"Masato Yoshihara","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Masato","middleName":"","lastName":"Yoshihara","suffix":""},{"id":216745992,"identity":"3c21f2a7-fcfa-4545-9500-aba437f4741e","order_by":5,"name":"Satoshi Tamauchi","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Tamauchi","suffix":""},{"id":216745993,"identity":"95793969-fa93-4091-9b5f-50811cac7064","order_by":6,"name":"Yusuke Shimizu","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Shimizu","suffix":""},{"id":216745994,"identity":"2b6a1fa5-c35a-4bf2-88b6-d7f577d91c47","order_by":7,"name":"Yoshiki Ikeda","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yoshiki","middleName":"","lastName":"Ikeda","suffix":""},{"id":216745995,"identity":"17545847-2d87-41bc-bd90-4e866856c0ab","order_by":8,"name":"Nobuhisa Yoshikawa","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nobuhisa","middleName":"","lastName":"Yoshikawa","suffix":""},{"id":216745996,"identity":"6eb11cd6-e17c-4491-8313-accf4d17db24","order_by":9,"name":"Kaoru Niimi","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kaoru","middleName":"","lastName":"Niimi","suffix":""},{"id":216745997,"identity":"0482ad06-9269-4199-8c34-0efc575efcfd","order_by":10,"name":"Shiro Suzuki","email":"","orcid":"","institution":"Aichi Cancer Center Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shiro","middleName":"","lastName":"Suzuki","suffix":""},{"id":216745998,"identity":"f89a0ff4-ebfb-4896-bf09-b1eac4bb80ab","order_by":11,"name":"Hiroaki Kajiyama","email":"","orcid":"","institution":"Nagoya University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hiroaki","middleName":"","lastName":"Kajiyama","suffix":""}],"badges":[],"createdAt":"2023-06-30 23:12:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3129590/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3129590/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":39924783,"identity":"8e754260-b4ce-4f96-ae36-5aa003f0e49d","added_by":"auto","created_at":"2023-07-12 14:51:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94344,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) The trends of blood hemoglobin levels in the olaparib group are shown. There were 30 cases of initial interruption of treatment due to anemia after the start of treatment. Treatment was interrupted when the hemoglobin level fell below 8 mg/dL. A total of 22/30 (73.3%) patients was interrupted within 4-12 weeks of treatment. (\u003cstrong\u003eb\u003c/strong\u003e) The trends of blood platelet levels in the niraparib group are shown. There were 16 cases of initial interruption of treatment due to thrombocytopenia after the start of treatment. Treatment was interrupted when the platelet level fell below 100,000 /µL. A total of 15/16 (73.3%) patients was interrupted within 8 weeks of treatment\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3129590/v1/839de7f2b23ce09b667c14a9.png"},{"id":39924784,"identity":"42f56a03-4c9d-4c0f-94f0-d541ba4ac458","added_by":"auto","created_at":"2023-07-12 14:51:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88444,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) Hemoglobin values in the olaparib group at the initial visit and at the start of treatment, and ratio of change of the two points are shown with and without interruption. (\u003cstrong\u003eb\u003c/strong\u003e) Platelet values in the niraparib group at the initial visit and at the start of treatment, and ratio of change of the two points are shown with and without interruption\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3129590/v1/a0de95b848cdb4e96db7734d.png"},{"id":40422738,"identity":"95b42648-8e4a-4e4f-9dce-4381a393aceb","added_by":"auto","created_at":"2023-07-23 01:02:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":449793,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3129590/v1/8093f4ad-a31b-4577-af1f-1662d99b3cc4.pdf"}],"financialInterests":"","formattedTitle":"Safety assessments and clinical features of PARP inhibitors from real-world data of Japanese patients with ovarian cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer is the third most common gynecologic malignancy and was the second leading cause of death from gynecologic cancer worldwide in 2020[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Epithelial ovarian cancer constitutes most ovarian malignancies, with most cases diagnosed at an advanced stage. The 5-year survival rate for ovarian cancer is approximately 30%. Despite achieving an approximately 80% response rate with standard treatment of optimal debulking surgery and platinum-based chemotherapy, most patients experience recurrence and disease progression within 2 y, leading to multiple recurrences and the development of platinum-resistant ovarian cancer[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Therefore, extending the progression-free period and improving the 5-year survival rate are urgent challenges.\u003c/p\u003e \u003cp\u003ePoly (ADP-ribose) polymerase (PARP) inhibitors have emerged as a significant breakthrough in managing advanced ovarian cancer in recent years[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. PARP is an enzyme crucial for repairing single-strand DNA breaks. PARP inhibitors are a class of drugs that block PARP enzyme activity, causing the accumulation of single-strand breaks, which eventually turn into double-strand breaks (DSBs). DSBs can be repaired by a homologous recombination repair (HRR) pathway. However, in cancer cells with \u003cem\u003eBRCA\u003c/em\u003e mutations or homologous recombination deficiency (HRD), the HRR pathway is already impaired. Thus, when PARP inhibitors are used to treat these cells, they further compromise DNA repair mechanisms by blocking the repair of single-strand breaks. This creates a state of synthetic lethality, as the combined effect of the impaired HRR pathway and PARP inhibition induces excessive DNA damage, causing cancer cell death [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Japan, olaparib has received approval for various maintenance treatments, including platinum-sensitive relapsed ovarian cancer in 2018[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], \u003cem\u003eBRCA\u003c/em\u003e mutations following remission of first-line platinum chemotherapy in 2019[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and HRD in combination with bevacizumab after remission of first-line platinum chemotherapy in 2020[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Conversely, niraparib was approved for maintenance treatment of platinum-sensitive relapsed ovarian cancer in 2020[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], maintenance treatment following remission of first-line platinum chemotherapy in 2020[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and monotherapy treatment of HRD and platinum-sensitive relapsed ovarian cancer after third or more chemotherapy sessions in 2020[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eSince eligibility criteria restrict patient enrollment in clinical trials and the adverse effects observed may vary due to racial differences, clinical trial results do not necessarily correspond to real-world practice. Thus, there is growing interest in using real-world data to answer clinical questions unanswerable through clinical trial data[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, accumulating real-world data may reveal findings unavailable in clinical trials or even overturn clinical trial data. Since maintenance therapy follows an initial treatment, accumulating the clinical data takes time. Olaparib and niraparib have been used for 5 and 2 y, respectively, in Japan. Therefore, we examined the real-world data on the safety of both drugs. Additionally, we assessed whether interruptions could be predicted and whether certain trends existed among patients who interrupted the drugs.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cp\u003e The records of 181 patients with ovarian cancer who received olaparib and/or niraparib treatment at Nagoya University Hospital (Nagoya, Japan) and Aichi Cancer Center Hospital (Nagoya, Japan) from May 2018 to December 2022 were retrospectively reviewed. Both the olaparib and niraparib groups included patients undergoing maintenance treatment for advanced epithelial ovarian, fallopian tube, or primary peritoneal cancer after first-line platinum-based chemotherapy and recurrent epithelial ovarian, fallopian tube, or primary peritoneal cancer after platinum-based chemotherapy. We investigated the patients\u0026rsquo; clinical information, including age, body mass index (BMI), smoking and drinking habits, histological type, \u003cem\u003eBRCA\u003c/em\u003e and HRD status, previous chemotherapy regimens, adverse effects, and blood sampling data, at several points. This study was approved by the ethics committee of each institute (Approval No. 2013-0078).\u003c/p\u003e \u003cp\u003eStatistical analyses were performed using GraphPad Prism 9, with the Mann\u0026ndash;Whitney U test used for comparisons between both groups. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eThe olaparib and niraparib groups comprised 131 and 50 patients, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median age was 59 (30\u0026ndash;80) in the olaparib group and 50 (23\u0026ndash;80) in the niraparib group, while the median BMI was 21.2 (14.2\u0026ndash;32.8) in the olaparib group and 21.9 (14.3\u0026ndash;30.4) in the niraparib group. There were no differences in smoking habits or diabetes between both groups, but alcohol consumption was higher in the niraparib group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01).\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\u003ePatient characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOlaparib (N\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNiraparib (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e 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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (30\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (23\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.2 (14.2\u0026ndash;32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9 (14.3\u0026ndash;30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistologic subtype\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (87.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (64.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClear\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarcinosarcoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBRCA\u003c/em\u003e status\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (52. 0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (52.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (44. 0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRD\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (83.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (66.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBMI, body mass index; DM, diabetes mellitus; HRD, homologous recombination deficiency\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe proportion of serous carcinoma was significantly higher in the olaparib group (115/131, 87.8%) compared to the niraparib group (32/50, 64.0%) (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The proportion of \u003cem\u003eBRCA\u003c/em\u003e-positive patients was 26/131 (19.8%) in the olaparib group and 2/50 (4.0%) in the niraparib group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05), while that of HRD-positive patients was 19/131 (14.5%) in the olaparib group and 4/50 (8.0%) in the niraparib group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.32). In addition, the \u003cem\u003eBRCA\u003c/em\u003e status was unknown for 69/131 (52.7%) patients in the olaparib group and 22/50 (44.0%) patients in the niraparib group. The HRD status was unknown for 110/131 (83.9%) patients in the olaparib group and 33/50 (66.0%) patients in the niraparib group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTreatment history\u003c/h2\u003e \u003cp\u003eThe patients\u0026rsquo; treatment history is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The median observation period was 697 (68\u0026ndash;1699) d in the olaparib group and 423 (66\u0026ndash;726) d in the niraparib group. The median treatment duration was 190 (14\u0026ndash;1667) d in the olaparib group and 203 (5\u0026ndash;726) d in the niraparib group. Treatment was discontinued due to adverse effects in 22/131 (16.8%) patients in the olaparib group and 6/50 (12.0%) patients in the niraparib group. The response to the most recent treatment was similar in both groups.\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\u003eTreatment history\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOlaparib (N\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNiraparib (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation days (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e697 (68\u0026ndash;1699)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e423 (66\u0026ndash;726)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration to the treatment (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (14\u0026ndash;1667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e203 (5\u0026ndash;726)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReason for termination\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (48.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (58.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdverse effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of previous chemotherapy regimens\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;~\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (87.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (98.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;~\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse to most recent treatment\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (47.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (54.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (52.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintenance for first-line chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (56.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment with Bev\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (13.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterruption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (64.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReason for interruption\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 \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeutropenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThrombocytopenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (20.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNausea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (16.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCR, complete response; PR, partial response; PD, progressive disease\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFurthermore, 31/131 (23.7%) in the olaparib group and 28/50 (56.0%) in the niraparib group received maintenance therapy following first-line chemotherapy. Maintenance therapy in combination with bevacizumab was administered to 18/131 (13.7%) patients in the olaparib group. Additionally, 5/131 (3.8%) patients in the olaparib group and 10/50 (20.0%) patients in the niraparib group were transferred to maintenance therapy without surgery (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Treatment was interrupted in 68/131 (51.9%) patients in the olaparib group and 32/50 (64.0%) patients in the niraparib group (p\u0026thinsp;=\u0026thinsp;0.87). The most common reason for treatment interruption based on blood data was anemia in 33/68 (48.5%) patients in the olaparib group and thrombocytopenia in 16/32 (50.0%) patients in the niraparib group. In the olaparib group, 20/68 (55.6%) patients interrupted treatment due to fatigue and/or nausea.\u003c/p\u003e \u003cp\u003eThe characteristics of cases where treatment was discontinued due to adverse effects in the early treatment stage are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A total of 13/131 (9.9%) patients in the olaparib group and 5/50 (10.0%) patients in the niraparib group discontinued treatment due to adverse effects within the first 3 months of treatment. The median treatment duration was 43 (14\u0026ndash;77) d in the olaparib group and 27 (5\u0026ndash;28) d in the niraparib group. The median BMI was 19.9 (14.2\u0026ndash;26.5) in the olaparib group and 20.5 (14.3\u0026ndash;24.9) in the niraparib group, indicating that both groups had a higher proportion of thin patients compared to the overall population. In both groups, most patients received maintenance therapy after recurrence. The most common reason for early treatment discontinuation was fatigue or vomiting in 8/13 (61.5%) patients in the olaparib group and thrombocytopenia in 3/5 (60.0%) patients in the niraparib group.\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\u003eThe characteristics of patients who discontinued treatment due to adverse effects within the first 3 months of treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOlaparib (N\u0026thinsp;=\u0026thinsp;131)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNiraparib (N\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiscontinued cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDuration to the treatment(days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (14\u0026ndash;154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (5\u0026ndash;28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.1 (14.2\u0026ndash;29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.5 (14.3\u0026ndash;24.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNumber of previous chemotherapy regimens\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1\u0026ndash;3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eResponse to most recent treatment\u003c/p\u003e \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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (69.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (80.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMaintenance for first-line chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eReason for termination\u003c/p\u003e \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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeutropenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThrombocytopenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (60.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFatigue, Vomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDysgeusia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInterstitial pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI, body mass index; DM, diabetes mellitus; CR, complete response; PR, partial response\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHematological data trends\u003c/h2\u003e \u003cp\u003eThe trends of blood hemoglobin and platelet levels, which were the most common causes of treatment interruption based on blood data, in the olaparib and niraparib groups, respectively, are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea. In the olaparib group, there were 30 cases of initial treatment interruption due to anemia after the start of treatment. Among these, 22/30 (73.3%) were interrupted within 4\u0026ndash;12 weeks of treatment. Conversely, there were 16 cases of initial treatment interruption due to thrombocytopenia in the niraparib group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Among these, 15/16 (93.8%) were interrupted within 8 weeks of treatment. Interruptions due to thrombocytopenia in the niraparib group tended to occur earlier than interruptions due to anemia in the olaparib group. As described above, the timing of interruptions showed certain trends and characteristics for each drug.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of interruption\u003c/h2\u003e \u003cp\u003ePredicting adverse effects in patients would enhance treatment management and ensure safe administration of the drug, leading to successful completion of the treatment. We hypothesized that the degree of adverse effects during chemotherapy might correlate with that during maintenance therapy using consecutive PARP inhibitors. Therefore, to predict treatment interruption due to hematological adverse effcts, blood collection data before treatment and after chemotherapy were investigated. Specifically, we compared the blood collection data at the initial visit and at the start of olaparib/niraparib treatment and the rate of change between the groups with and without interruption. The results for interruption due to anemia in the olaparib group are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea. No significant differences existed between both groups, and predicting interruption due to anemia from the blood data at the initial visit or the start of treatment was challenging. The results for interruption due to thrombocytopenia in the niraparib group are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb. No significant differences existed between both groups, and predicting interruption due to thrombocytopenia from the blood data at the initial visit or the start of treatment was challenging. Both olaparib-induced interruption due to anemia and niraparib-induced interruption due to thrombocytopenia were difficult to predict from the blood data.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDue to the high recurrence rate and low survival rate of ovarian cancer, as well as the limited availability of drugs other than chemotherapy in the past, the emergence of PARP inhibitors has brought hope for ovarian cancer treatment[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We aimed to explore the real-world data of olaparib and niraparib in Japan, as both agents target the same pathways but are used differently. Olaparib is primarily used as a single agent in maintenance therapy after first-line chemotherapy for \u003cem\u003eBRCA\u003c/em\u003e-positive patients, based on the SOLO-1 study[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and in combination with bevacizumab for HRD patients, based on the PAOLA-1 study[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Conversely, niraparib can be used regardless of biomarkers, based on the PRIMA study[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. \u003cem\u003eBRCA\u003c/em\u003e mutations and HRD are frequently observed in high-grade serous ovarian carcinoma[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], suggesting that the niraparib group may have had fewer patients with serous carcinoma, \u003cem\u003eBRCA\u003c/em\u003e-positive status, and HRD. The complete response rate after the most recent platinum-based chemotherapy was 47.3% in the olaparib group and 54.0% in the niraparib group. When limited to patients receiving maintenance therapy after first-line chemotherapy, the rate was 93.5% in the olaparib group and 60.7% in the niraparib group, similar to prior studies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, there were differences in adverse effects between the olaparib group and the niraparib group. Despite sharing the same pharmacological mechanism, the toxicity profile is different for both agents[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The differences in adverse effects of these agents could be attributed to dosage schedule, half-life, drug interactions, and metabolism[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In this study, Grade 3 or 4 adverse reactions in the olaparib group included anemia (25.2%), neutropenia (14.5%), thrombocytopenia (3.8%), and fatigue/nausea (15.3%), occurring more frequently than in previous studies [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This discrepancy might be because the Japanese have a lower BMI than Westerners. Conversely, Grade 3 or 4 adverse reactions in the niraparib group comprised anemia (14.0%), neutropenia (10.0%), thrombocytopenia (32.0%), and fatigue/nausea (6.0%), respectively, with these results either being the same or less frequent than in previous studies[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This may be because the starting dose for niraparib was individualized based on body weight and platelet count. Previous studies started with a fixed dose of 300 mg, and the NOVA trial results led to the individualization of the initial dose according to body weight and platelet count. Moreover, recently published data from the NORA trial confirmed that dose individualization is associated with improved hematologic toxicity[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThrombocytopenia is a peculiar toxicity observed in niraparib treatment, and we showed that niraparib-induced thrombocytopenia occurs earlier than olaparib-induced anemia. Furthermore, there were three cases where platelet levels did not recover after treatment interruption, leading to the discontinuation of the drug. This finding suggests that niraparib-induced thrombocytopenia may be more robust than olaparib-induced anemia. Among patients who discontinued treatment due to adverse effects, 59% in the olaparib group and 100% in the niraparib group discontinued within the first 3 months of treatment. It was considered that thin patients with several previous regimens should be managed with particular attention to adverse effects early in the treatment. Furthermore, careful long-term management of adverse effects is crucial, especially when treated with olaparib.\u003c/p\u003e \u003cp\u003eWhile there have been many reports on the adverse effects of PARP inhibitor therapy[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], no reports describing their predictability exist. This is the first study on the predictability of interruptions in PARP inhibitor therapy using blood collection data. However, the blood toxicity of both agents was difficult to predict using blood collection data. Generally, hematological adverse events associated with PARP inhibitors are frequent but transient, occurring during the first months of therapy, and are often resolved with dose reduction. We also observed hematological adverse events in the later treatment stages, especially in the olaparib group, and rare complications such as myelodysplastic syndrome and acute myeloid leukemia[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Thus, regular blood tests should be conducted even after the initial months of treatment.\u003c/p\u003e \u003cp\u003eIn conclusion, we examined the real-world data on the safety of olaparib and niraparib, as well as the predictability of intake interruption based on blood sampling data. Patient backgrounds and toxicity profiles differed between the olaparib and niraparib groups. However, predicting the blood toxicity of both agents using blood collection data was challenging. This study revealed the characteristics of the patients and the timing of interruption for each drug and highlighted the importance of carefully managing adverse effects, particularly during the early treatment stages.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express the highest appreciation to the entire staff of the Department of Obstetrics and Gynecology, Nagoya University Graduate School of Medicine, and\u0026nbsp;Department of Gynecology, Aichi Cancer Center.\u0026nbsp;This work was supported by JSPS KAKENHI Grant Number 21H03075 and the Princess Takamatsu Cancer Research Fund (No. 20-25237), Moreover, this study was also supported by Program for Tokai Pathway to Global Excellence (T-GEx) FY2021 and for Promoting the Enhancement of Research Universities as young researcher units for the advancement of new and undeveloped fields at Nagoya University. Furthermore, we thank Enago (https://www.enago.jp/) for English language editing of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData availability statements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Data collection and analysis were performed by R.U., E.W., and A.Y. The first draft of the manuscript was written by R.U. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F (2021) Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71 (3):209-249. doi:10.3322/caac.21660\u003c/li\u003e\n\u003cli\u003ePignata S, S CC, Du Bois A, Harter P, Heitz F (2017) Treatment of recurrent ovarian cancer. Ann Oncol 28 (suppl_8):viii51-viii56. doi:10.1093/annonc/mdx441\u003c/li\u003e\n\u003cli\u003eKim A, Ueda Y, Naka T, Enomoto T (2012) Therapeutic strategies in epithelial ovarian cancer. 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Lancet Oncol 20 (1):e15-e28. doi:10.1016/S1470-2045(18)30786-1\u003c/li\u003e\n\u003cli\u003eStemmer A, Shafran I, Stemmer SM, Tsoref D (2020) Comparison of Poly (ADP-ribose) Polymerase Inhibitors (PARPis) as Maintenance Therapy for Platinum-Sensitive Ovarian Cancer: Systematic Review and Network Meta-Analysis. Cancers (Basel) 12 (10). doi:10.3390/cancers12103026\u003c/li\u003e\n\u003cli\u003eMorice PM, Leary A, Dolladille C, Chretien B, Poulain L, Gonzalez-Martin A, Moore K, O\u0026apos;Reilly EM, Ray-Coquard I, Alexandre J (2021) Myelodysplastic syndrome and acute myeloid leukaemia in patients treated with PARP inhibitors: a safety meta-analysis of randomised controlled trials and a retrospective study of the WHO pharmacovigilance database. Lancet Haematol 8 (2):e122-e134. doi:10.1016/S2352-3026(20)30360-4\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Ovarian cancer, PARP inhibitors, olaparib, niraparib, adverse effects","lastPublishedDoi":"10.21203/rs.3.rs-3129590/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3129590/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePoly (ADP-ribose) polymerase (PARP) inhibitors, such as olaparib and niraparib, have been increasingly used in ovarian cancer treatment. However, the real-world safety data of these drugs in Japanese patients and the predictability of treatment interruptions are limited.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective study included 181 patients with ovarian cancer who received olaparib or niraparib at two independent hospitals in Japan between May 2018 and December 2022. Clinical information and blood sampling data were collected. Patient characteristics, treatment history, and hematological data trends were compared, and the predictability of treatment interruptions based on blood sampling data was examined.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eRegarding patient backgrounds, the olaparib group had higher proportions of patients with serous carcinoma, \u003cem\u003eBRCA\u003c/em\u003e positivity, homologous recombination deficiency, and those receiving maintenance therapy after recurrence treatment than the niraparib group. Regarding toxicity properties, the most common reasons for discontinuation in the olaparib group were anemia, fatigue, and nausea, while discontinuation was primarily due to thrombocytopenia in the niraparib group. Thrombocytopenia caused by niraparib treatment occurred earlier than anemia caused by olaparib treatment. Patients with a low body mass index or who had undergone several previous treatment regimens were more likely to discontinue treatment due to adverse effects within the first 3 months. Although we analyzed blood collection data, predicting treatment interruptions due to blood toxicity using blood data was challenging.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this study, we revealed the characteristics of patients and the timing of interruptions for each drug, highlighting the importance of carefully managing adverse effects, particularly during the early treatment stages.\u003c/p\u003e","manuscriptTitle":"Safety assessments and clinical features of PARP inhibitors from real-world data of Japanese patients with ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-12 14:51:11","doi":"10.21203/rs.3.rs-3129590/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":"606db87d-bb18-4c29-9fa1-80a476136c82","owner":[],"postedDate":"July 12th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-02T11:14:22+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-12 14:51:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3129590","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3129590","identity":"rs-3129590","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}