Impact of Neurokinin-1 Receptor Antagonists on New-Onset Diabetes in Patients Receiving Chemotherapy: A Retrospective Cross-Sectional Study Using Health Claims Database in Japan

Impact of Neurokinin-1 Receptor Antagonists on New-Onset Diabetes in Patients Receiving Chemotherapy: A Retrospective Cross-Sectional Study Using Health Claims Database in Japan | 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 Impact of Neurokinin-1 Receptor Antagonists on New-Onset Diabetes in Patients Receiving Chemotherapy: A Retrospective Cross-Sectional Study Using Health Claims Database in Japan Yuki Ozawa, Shinya Suzuki, Takuma Koinuma, Takashi Yokokawa, Takenori Ichimura, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9079117/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Purpose We aimed to optimize antiemetic strategies by evaluating the impact of neurokinin-1 receptor antagonist (NK1-RA) administration along with dexamethasone on new-onset diabetes in patients receiving chemotherapy. Methods This retrospective cross-sectional study was conducted using the DeSC database and included patients aged ≥ 18 years with solid tumors who initiated parenteral anticancer agents and dexamethasone between April 2014 and March 2023. Patients with a history of diabetes or hematologic malignancies were excluded. The primary outcome was new-onset diabetes during the 2 months following the index month, defined by International Classification of Diseases, Tenth Revision codes or prescription data. Multivariable logistic regression assessed the association between NK1-RA administration along with dexamethasone and new-onset diabetes. Results Among 71,539 eligible patients, 51.1% received NK1-RAs. NK1-RA administration along with dexamethasone was significantly associated with an increased risk of new-onset diabetes (adjusted odds ratio: 1.43; 95% confidence interval: 1.31–1.55; p < 0.001). Sensitivity analyses demonstrated consistent results across different evaluation periods and outcome definitions. Conclusion NK1-RA administration along with dexamethasone was associated with an increased risk of new-onset diabetes, likely due to a drug–drug interaction that increases dexamethasone concentrations. These findings suggest the need to optimize antiemetic strategies, including sparing NK1-RAs or reducing the dexamethasone dose to minimize unnecessary steroid potentiation. neurokinin-1 receptor antagonist dexamethasone diabetes drug-drug interaction chemotherapy Figures Figure 1 Figure 2 Introduction Chemotherapy-induced nausea and vomiting (CINV) is a major adverse event of chemotherapy and reduces patients’ quality of life [ 1 ]. Recent advances in antiemetic therapy have improved CINV control. The overall complete response rate for cisplatin-based highly emetogenic chemotherapy (HEC) reached 78% with the use of four antiemetic agents—olanzapine, neurokinin-1 receptor antagonist (NK1-RA), 5-hydroxytryptamine type 3 serotonin receptor antagonist (5HT3-RA), and dexamethasone—compared with 52.3% 20 years ago [ 2 , 3 ]. With improved CINV control, attention has shifted to the risks associated with antiemetics, promoting strategies such as steroid sparing [ 4 – 6 ]. Dexamethasone, when used as an antiemetic during chemotherapy, causes several adverse effects, including diabetes, decreased bone mineral density, insomnia, and agitation [ 7 – 9 ]. In addition to steroid-related adverse effects, drug–drug interactions (DDIs) involving NK1-RAs are another major concern. NK1-RAs are moderate cytochrome P450 3A4 (CYP3A4) inhibitors, and clinically significant DDIs have been reported, including respiratory depression in patients receiving oxycodone with an NK1-RA [ 10 ] and severe somnolence with quetiapine [ 11 ]. These events are likely attributable to increased drug concentrations resulting from CYP3A4 inhibition. In addition, a systematic review of DDIs related to aprepitant and fosaprepitant indicates that dexamethasone, which is routinely co-administered with an NK1-RA, is a particularly significant interaction pair [ 12 ]. This combination doubled the area under the concentration–time curve of dexamethasone [ 13 ]. Despite the clinical significance of this interaction, no consensus exists regarding the optimal dexamethasone dose when co-administered with NK1-RAs. Some international guidelines, such as those from the American Society of Clinical Oncology and the National Comprehensive Cancer Network, recommend adjusted dexamethasone doses for HEC regimens [ 14 , 15 ]. However, the Multinational Association of Supportive Care in Cancer and European Society for Medical Oncology Joint Guideline does not provide specific recommendations on dexamethasone dose reduction [ 16 ]. Moreover, for less than moderately emetogenic chemotherapy, there is even less consensus regarding optimal antiemetic strategies. This lack of consensus may be due to the fact that available interaction evidence is largely limited to pharmacokinetic data [ 13 ]; therefore, the clinical consequences of the DDI between NK1-RAs and dexamethasone remain unclear. Clarifying these outcomes would provide a rationale for optimizing antiemetic strategies, including sparing NK1-RAs or reducing the dexamethasone dose. A representative adverse effect of dexamethasone is diabetes. A previous study suggests that even short-term administration as an antiemetic can cause diabetes, and the risk increases with higher cumulative doses [ 7 ]. Therefore, we hypothesized that increased dexamethasone concentrations resulting from NK1-RA co-administration might impact the development of diabetes. A previous meta-analysis also suggests an association between diabetes and cancer mortality [ 17 ], underscoring its clinical significance. We aimed to optimize antiemetic strategies by evaluating the impact of NK1-RA administration along with dexamethasone for CINV on new-onset diabetes using large-scale health claims data. Methods Study design and setting This retrospective cross-sectional study was conducted using the DeSC database (DeSC Healthcare Inc., Japan). Several studies have used this database [ 18 – 20 ]. The database contains anonymized claims data for over 3 million patients with cancer recorded between April 2014 and October 2023. It includes three insurance systems: health insurance for corporate employees, National Health Insurance for self-employed and unemployed individuals, and the Medical Care System for the Advanced Elderly for those aged ≥ 75 years. Individual patients are uniquely identified across insurers through health care institutions, allowing longitudinal tracking. The patient enrollment period spanned from April 2014 to March 2023, with the outcome assessment period defined as the 2 months following the index month. The study design diagram is shown in Fig .1. Because we evaluated the association within a fixed short-term window without considering censoring, it was defined as cross-sectional, although new-onset diabetes was assessed after chemotherapy initiation. The study protocol was approved by the Ethics Committee of Tokyo University of Pharmacy and Life Sciences (approval number: 2025-033). This study followed the Reporting of Studies Conducted Using Observational Routinely Collected Health Data for Pharmacoepidemiology (RECORD-PE) statement. Participants Eligibility criteria included patients aged ≥ 18 years with solid tumors who received parenteral anticancer agents along with dexamethasone. These anticancer agents were identified using Anatomical Therapeutic Chemical (ATC) code L and were individually reviewed to ensure clinical relevance. The index month was defined as the first month in which a patient received these anticancer agents within the database between April 2014 and March 2023. We adopted a new-user design with a 6-month washout period to eliminate prevalent user bias. Exclusion criteria were: (1) diabetes during the index month or in the 6 months prior, (2) hematologic malignancy during the index month, and (3) no dexamethasone administration during the 3 months after the index month. Diabetes was defined using International Classification of Diseases 10th Revision (ICD-10) codes (E10.x–E14.x) or prescription data (ATC code A10). Hematologic malignancy was defined using ICD-10 codes for malignant neoplasms (C81.x–C96.x). Outcomes The primary outcome was new-onset diabetes during the 2 months following the index month. Based on a previous validation study [ 21 ], new-onset diabetes was defined using ICD-10 codes (E11.x–E14.x) excluding type 1 diabetes, or prescription data (ATC code A10). To exclude prevalent cases, patients with diabetes diagnosis during the index month were excluded. Accordingly, incidence was evaluated over the subsequent two months (month 1 and month 2). The assessment period of 3 months was defined based on a previous study [ 7 ]. Secondary outcomes included the frequency and timing of new-onset diabetes. Variables Variables that could potentially affect the outcome were selected. Age was categorized as < 70 or ≥ 70 years at the index month. Sex was classified as male or female. Comorbidities, including hypertension, hyperuricemia, dyslipidemia, depression, and insomnia, were defined using ICD-10 codes during the index month or in the 6 months prior (Online Resource 1). Pancreatic cancer was identified using ICD-10 codes (C25.x) during the index month to define the population initiating chemotherapy. The Charlson Comorbidity Index (CCI) was calculated based on a previously validated study [ 22 ], using ICD-10 codes recorded during the index month or in the 6 months prior (Online Resource 2). NK1-RAs, including aprepitant, fosaprepitant, and fosnetupitant, were identified using ATC code A04AD. Concomitant medications included olanzapine and systemic steroids other than dexamethasone, identified using ATC codes (N05AH03; H02AB excluding H02AB02 [dexamethasone] and H02AB08 [triamcinolone]) during the index month and the subsequent 2 months. Dexamethasone was identified using ATC code H02AB02, and the total dose during the index month and subsequent 2 months was calculated. Surgery was defined using treatment codes for general anesthesia and endotracheal intubation recorded during the index month or in the 6 months prior. Most variables were selected based on previous studies [ 23 – 27 ], while others were chosen based on clinical relevance. Specifically, the CCI score was included as a validated measure of overall comorbidity burden. Olanzapine was included as an exploratory variable because its use is contraindicated in patients with diabetes in Japan and may influence both prescribing patterns and diabetes risk. Statistical analysis Continuous variables were summarized using the mean and standard deviation. Categorical variables were summarized as frequencies and percentages. Missing data were not imputed because the study relied on claims-based diagnostic and procedural codes, for which the absence of a code was assumed to indicate the absence of the condition or treatment. For the primary analysis, multivariable logistic regression was used to assess the association between NK1-RA administration along with dexamethasone and new-onset diabetes. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values were calculated for each variable. New-onset diabetes was defined as the dependent variable, and the covariates described above were included as independent variables. Sensitivity analyses were conducted by (1) restricting the outcome definition to both ICD-10 codes and prescription data to increase diagnostic specificity, (2) extending the assessment period to 6 months, and (3) excluding covariates with high ORs. Due to the exploratory nature of this study, a sample size calculation was not performed. A two-sided p-value < 0.05 was considered statistically significant. All statistical analyses were performed using R software, version 4.5.0. Results Participants flow and characteristics The participant flow is shown in Fig. 2 . During the enrollment period, 252,056 patients were initially identified. Of these, 180,517 patients were excluded: 74,391 were excluded due to an insufficient look-back period; 78,571 had a history of diabetes; 8,067 had hematologic malignancies; and 19,488 had not received dexamethasone. Consequently, 71,539 patients were included in the analysis. Patient characteristics are summarized in Table 1 . During the 3-month assessment period, the mean duration of chemotherapy was 2.51 months. NK1-RAs were administered to 51.1% of patients, with a mean duration of 2.32 months. Table 1 Participant characteristics Age (years), mean (SD) N = 71,539 69.6 (10.6) Sex (male / female), n (%) 36,332 (50.8) / 35,207 (49.2) Comorbidity Hypertension, n (%) 33,735 (47.2) Hyperuricemia, n (%) 6,443 (9.0) Dyslipidemia, n (%) 22,173 (31.0) Depression, n (%) 3731 (5.2) Insomnia, n (%) 19,193 (26.8) Pancreatic cancer, n (%) 4,796 (6.7) CCI score without cancer ≥ 1, n (%) 46967 (65.7) Concomitant medication NK1-RA, n (%) 36,583 (51.1) Olanzapine, n (%) 4,841 (6.8) Total dose of dexamethasone, mg mean (SD) 51.2 (35.8) Steroid except dexamethasone, n (%) 9,928 (13.9) Surgery before chemotherapy, n (%) 25,489 (35.6%) CCI Charlson comorbidity index, NK1-RA neurokinin 1 receptor antagonist, SD standard deviation. Primary outcome The association between NK1-RA administration along with dexamethasone and new-onset diabetes is shown in Table 2 . NK1-RA administration was significantly associated with new-onset diabetes (OR: 1.43; 95% CI: 1.31–1.55). Table 2 Multivariable logistic regression analysis for new-onset diabetes Age ≥ 70 Odds ratio 95% confidence interval p -value 1.07 0.98–1.16 0.142 Sex (female) 0.69 0.63–0.75 < 0.001 Hypertension 1.23 1.13–1.34 < 0.001 Hyperuricemia 1.03 0.90–1.16 0.682 Dyslipidemia 1.11 1.02–1.22 0.015 Depression 1.01 0.84–1.20 0.93 Insomnia 0.92 0.84–1.00 0.061 Pancreatic cancer 4.19 3.77–4.66 < 0.001 CCI score without cancer ≥ 1 1.15 1.05–1.26 0.003 NK1-RA 1.43 1.31–1.55 < 0.001 Olanzapine 1.15 0.99–1.33 0.06 Total dose of dexamethasone ≥ 50 mg 1.09 1.00–1.19 0.04 Steroid except dexamethasone 3.04 2.79–3.30 < 0.001 Surgery before chemotherapy 0.51 0.46–0.57 < 0.001 CCI Charlson comorbidity index, NK1-RA neurokinin 1 receptor antagonist. Other factors significantly associated with new-onset diabetes included age ≥ 70 years, hypertension, dyslipidemia, pancreatic cancer, a CCI score excluding cancer ≥ 1, a total dexamethasone dose ≥ 50 mg, and the use of systemic steroids other than dexamethasone. In contrast, female sex and prior surgery were significantly associated with a decreased risk of new-onset diabetes. Secondary outcomes Regarding the frequency and timing of new-onset diabetes, 2,826 patients (4.0%) developed diabetes during the assessment period. Of these, 1,366 cases occurred in the month following the index month (month 1), and 1,460 cases occurred in the subsequent month (month 2). Sensitivity analysis Four sensitivity analyses were conducted. When the definition of new-onset diabetes was narrowed to cases identified by both ICD-10 codes and prescription data, NK1-RA administration remained significantly associated with new-onset diabetes (OR: 1.36; 95% CI: 1.13–1.64; Online Resource 3). Similarly, significant associations were observed when the assessment period was extended to 6 months (OR: 1.37; 95% CI: 1.29–1.46; Online Resource 4) and when covariates with high ORs, including pancreatic cancer or systemic steroids other than dexamethasone, were excluded (OR: 1.14; 95% CI: 1.05–1.23, and OR: 1.45; 95% CI: 1.28–1.51, respectively; Online Resources 5 and 6). Across all sensitivity analyses, pancreatic cancer, systemic steroids other than dexamethasone, and the CCI score remained consistently associated with new-onset diabetes, while female sex and prior surgery remained significantly associated with a decreased risk (Online Resources 3–6). Discussion Our findings suggest that NK1-RA administration along with dexamethasone for CINV is associated with an increased risk of new-onset diabetes, and this demonstrated high robustness across multiple sensitivity analyses. To our knowledge, this study is the first to investigate the association between NK1-RA administration along with dexamethasone for CINV and new-onset diabetes. These findings highlight a previously unrecognized safety signal associated with NK1-RAs and may provide an opportunity to reconsider and optimize antiemetic strategies. The cross-sectional design limits causal inference; however, several considerations support the plausibility of the observed association. Previous studies have identified several risk factors for CINV; however, diabetes has not been reported as one of them [ 28 ]. Furthermore, current clinical guidelines do not recommend prioritizing NK1-RA administration or intensifying antiemetic therapy specifically for patients with diabetes [ 14 – 16 ]. Therefore, baseline selection bias is unlikely. In addition, among patients receiving NK1-RAs, the duration of administration accounted for most of the 3-month assessment period, further supporting the observed association between NK1-RA administration and new-onset diabetes. The frequency of diabetes during HEC (57.1%) and moderately emetogenic chemotherapy (42.9%) has been reported in a previous study [ 7 ]. In that study, 14.3% of patients with cancer and no history of diabetes developed diabetes within 3 months after starting chemotherapy. Furthermore, 50.6% of patients developed insulin resistance, compared with 28.6% at baseline. These rates are higher than those observed in our study (4.0%), likely because of differences in data collection methods. We relied on health claims data, whereas the previous study used blood test data, such as homeostasis model assessment of insulin resistance, fasting plasma glucose, 2-h postprandial glucose, and hemoglobin A1c. Therefore, if laboratory data had been available in our analysis, additional cases of new-onset diabetes might have been identified, potentially resulting in a higher OR. However, this possibility remains unclear. Our proposed mechanism is that the DDI between NK1-RAs and dexamethasone increases dexamethasone concentrations. Co-administration of NK1-RAs has been reported to double the area under the concentration–time curve of dexamethasone through inhibition of CYP3A4 [ 13 ]. As noted earlier, dexamethasone used as an antiemetic drug during chemotherapy can lead to the development of diabetes [ 7 ]. Therefore, increased dexamethasone exposure may facilitate the development of diabetes as an adverse effect. This pharmacokinetic interaction may have contributed to the association observed in our study. In basic research, the NK1 receptor and its ligand, substance P, are involved in blood glucose regulation [ 29 ]. However, the underlying mechanisms are complex and remain controversial. Some studies suggest that NK1-RAs may prevent diabetes [ 30 ], while others report a potential increase in risk [ 31 ]. Therefore, the direct effect of NK1-RAs on glucose metabolism remains unclear. Taken together, the DDI between NK1-RAs and dexamethasone is a plausible mechanism for new-onset diabetes. This study has some limitations. First, because of the nature of health claims data, we could not adjust for important variables such as body mass index, diet, exercise habits, and family history of diabetes. Second, the use of a washout period to define new users may have reduced the number of patients aged ≥ 75 years, when many patients transition to the Medical Care System for the Advanced Elderly. This might have resulted in slight differences between our study population and the general age distribution. In conclusion, we suggest an association between NK1-RA administration along with dexamethasone for CINV and new-onset diabetes. This finding provides an opportunity to further optimize antiemetic therapies, such as sparing NK1-RAs or reducing the dexamethasone dose to mitigate unnecessary steroid potentiation. Given the potential clinical implications for antiemetic decision-making, future research is needed to clarify causality using alternative study designs, such as cohort studies, as well as to identify patient populations at high risk for developing diabetes. Declarations Author contributions YO is the principal investigator. YO and SS contributed to the conception of the study. YO, SS, TK and SI designed the study. YO, SS, TK, TY, TI, KS, YH and SI performed data interpretation. YO, SS and TK contributed to data management and statistical analysis. YO drafted the original manuscript. All authors read and approved the final version of the manuscript. Funding This study did not receive any external funding. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that there are no conflicts of interest related to this work. Ethics approval This study was reviewed and approved by the ethics committee of Tokyo University of Pharmacy and Life Sciences (approval number: 2025-033). Consent to participate Not applicable due to the use of anonymized health claims data. Consent for publication Not applicable. Acknowledgements We are grateful to Editage (www.editage.com) for English language editing. References Glaus A, Knipping C, Morant R, et al (2004) Chemotherapy-induced nausea and vomiting in routine practice: A European perspective. 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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-9079117","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630838112,"identity":"fce16c70-a935-4817-8a92-9f51360a1545","order_by":0,"name":"Yuki Ozawa","email":"","orcid":"","institution":"Tokyo University of Pharmacy and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Ozawa","suffix":""},{"id":630838113,"identity":"3e0c0fbc-351f-48ed-beb0-83a5439482c3","order_by":1,"name":"Shinya 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Takuma","middleName":"","lastName":"Koinuma","suffix":""},{"id":630838115,"identity":"88e7659d-6953-40a0-a361-d7d78355e0cf","order_by":3,"name":"Takashi Yokokawa","email":"","orcid":"","institution":"Tokyo University of Pharmacy and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Takashi","middleName":"","lastName":"Yokokawa","suffix":""},{"id":630838116,"identity":"cfda6d06-1019-44b6-8d1b-3b5ae723733e","order_by":4,"name":"Takenori Ichimura","email":"","orcid":"","institution":"Tokyo University of Pharmacy and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Takenori","middleName":"","lastName":"Ichimura","suffix":""},{"id":630838117,"identity":"0a4efea0-b9d6-484c-9a02-e93365825fc5","order_by":5,"name":"Kenichi Suzuki","email":"","orcid":"","institution":"Tokyo University of Pharmacy and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kenichi","middleName":"","lastName":"Suzuki","suffix":""},{"id":630838118,"identity":"4b077acb-a1a3-481f-9dea-e695f95b8094","order_by":6,"name":"Yusuke Hori","email":"","orcid":"","institution":"Tokyo University of Pharmacy and Life Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yusuke","middleName":"","lastName":"Hori","suffix":""},{"id":630838119,"identity":"08845db1-d48b-4e95-ad65-e61fcb177df3","order_by":7,"name":"Shinobu Imai","email":"","orcid":"","institution":"Showa University School of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Shinobu","middleName":"","lastName":"Imai","suffix":""}],"badges":[],"createdAt":"2026-03-10 04:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9079117/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9079117/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108950309,"identity":"709a59b6-83e6-4ceb-9e96-2262649f8f71","added_by":"auto","created_at":"2026-05-11 07:05:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":134307,"visible":true,"origin":"","legend":"\u003cp\u003eDesign diagram\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCCI\u003c/em\u003e Charlson comorbidity index,\u003cem\u003e NK1-RA\u003c/em\u003e neurokinin 1 receptor antagonist.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/2e9f7ccba66c772307f7b1e6.png"},{"id":108977764,"identity":"3ef87fde-8fdd-4015-b259-fd86f7a081d5","added_by":"auto","created_at":"2026-05-11 11:32:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":82600,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant flow diagram\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/17f9f0d926ecbbdb7152c9f8.png"},{"id":108979748,"identity":"3c68f534-f773-4df1-9770-0863d8bf2ee1","added_by":"auto","created_at":"2026-05-11 12:01:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":439653,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/c6660c20-b4bd-4dcf-99a9-6e7920a9b624.pdf"},{"id":108950313,"identity":"e30bf17c-40fd-4b0c-b097-0fe07d356658","added_by":"auto","created_at":"2026-05-11 07:05:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19829,"visible":true,"origin":"","legend":"","description":"","filename":"ESM1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/c14d3404ca5c83008c24e8fd.docx"},{"id":108977844,"identity":"60a594a3-387e-481c-b42b-fb6c5823e9a0","added_by":"auto","created_at":"2026-05-11 11:33:10","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19586,"visible":true,"origin":"","legend":"","description":"","filename":"ESM2.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/2f91377571c10d7ca9471270.docx"},{"id":108950312,"identity":"9eb6a2ca-f3fe-4d6d-bbfb-2acc97c8895d","added_by":"auto","created_at":"2026-05-11 07:05:04","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19659,"visible":true,"origin":"","legend":"","description":"","filename":"ESM3.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/7879556e2dfc42b0e8555166.docx"},{"id":108950315,"identity":"a01325c2-30cf-43a7-a86a-57c852e53441","added_by":"auto","created_at":"2026-05-11 07:05:05","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":19663,"visible":true,"origin":"","legend":"","description":"","filename":"ESM4.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/7cb2d1a2a246941c2269e318.docx"},{"id":108950316,"identity":"b0b45af1-a907-4d5d-aa05-fb6c501fdac4","added_by":"auto","created_at":"2026-05-11 07:05:05","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":19563,"visible":true,"origin":"","legend":"","description":"","filename":"ESM5.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/c25438ea168e66e469e74a2e.docx"},{"id":108950314,"identity":"f20a97c8-940f-47c9-aad8-4dc29a069f7e","added_by":"auto","created_at":"2026-05-11 07:05:05","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":19547,"visible":true,"origin":"","legend":"","description":"","filename":"ESM6.docx","url":"https://assets-eu.researchsquare.com/files/rs-9079117/v1/ec70dc77fa25558ac4d4a6b9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Neurokinin-1 Receptor Antagonists on New-Onset Diabetes in Patients Receiving Chemotherapy: A Retrospective Cross-Sectional Study Using Health Claims Database in Japan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChemotherapy-induced nausea and vomiting (CINV) is a major adverse event of chemotherapy and reduces patients\u0026rsquo; quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recent advances in antiemetic therapy have improved CINV control. The overall complete response rate for cisplatin-based highly emetogenic chemotherapy (HEC) reached 78% with the use of four antiemetic agents\u0026mdash;olanzapine, neurokinin-1 receptor antagonist (NK1-RA), 5-hydroxytryptamine type 3 serotonin receptor antagonist (5HT3-RA), and dexamethasone\u0026mdash;compared with 52.3% 20 years ago [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. With improved CINV control, attention has shifted to the risks associated with antiemetics, promoting strategies such as steroid sparing [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Dexamethasone, when used as an antiemetic during chemotherapy, causes several adverse effects, including diabetes, decreased bone mineral density, insomnia, and agitation [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to steroid-related adverse effects, drug\u0026ndash;drug interactions (DDIs) involving NK1-RAs are another major concern.\u003c/p\u003e \u003cp\u003eNK1-RAs are moderate cytochrome P450 3A4 (CYP3A4) inhibitors, and clinically significant DDIs have been reported, including respiratory depression in patients receiving oxycodone with an NK1-RA [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and severe somnolence with quetiapine [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These events are likely attributable to increased drug concentrations resulting from CYP3A4 inhibition. In addition, a systematic review of DDIs related to aprepitant and fosaprepitant indicates that dexamethasone, which is routinely co-administered with an NK1-RA, is a particularly significant interaction pair [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This combination doubled the area under the concentration\u0026ndash;time curve of dexamethasone [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite the clinical significance of this interaction, no consensus exists regarding the optimal dexamethasone dose when co-administered with NK1-RAs. Some international guidelines, such as those from the American Society of Clinical Oncology and the National Comprehensive Cancer Network, recommend adjusted dexamethasone doses for HEC regimens [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the Multinational Association of Supportive Care in Cancer and European Society for Medical Oncology Joint Guideline does not provide specific recommendations on dexamethasone dose reduction [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, for less than moderately emetogenic chemotherapy, there is even less consensus regarding optimal antiemetic strategies. This lack of consensus may be due to the fact that available interaction evidence is largely limited to pharmacokinetic data [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]; therefore, the clinical consequences of the DDI between NK1-RAs and dexamethasone remain unclear. Clarifying these outcomes would provide a rationale for optimizing antiemetic strategies, including sparing NK1-RAs or reducing the dexamethasone dose.\u003c/p\u003e \u003cp\u003eA representative adverse effect of dexamethasone is diabetes. A previous study suggests that even short-term administration as an antiemetic can cause diabetes, and the risk increases with higher cumulative doses [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, we hypothesized that increased dexamethasone concentrations resulting from NK1-RA co-administration might impact the development of diabetes. A previous meta-analysis also suggests an association between diabetes and cancer mortality [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], underscoring its clinical significance.\u003c/p\u003e \u003cp\u003eWe aimed to optimize antiemetic strategies by evaluating the impact of NK1-RA administration along with dexamethasone for CINV on new-onset diabetes using large-scale health claims data.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study was conducted using the DeSC database (DeSC Healthcare Inc., Japan). Several studies have used this database [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The database contains anonymized claims data for over 3\u0026nbsp;million patients with cancer recorded between April 2014 and October 2023. It includes three insurance systems: health insurance for corporate employees, National Health Insurance for self-employed and unemployed individuals, and the Medical Care System for the Advanced Elderly for those aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years. Individual patients are uniquely identified across insurers through health care institutions, allowing longitudinal tracking. The patient enrollment period spanned from April 2014 to March 2023, with the outcome assessment period defined as the 2 months following the index month. The study design diagram is shown in Fig .1. Because we evaluated the association within a fixed short-term window without considering censoring, it was defined as cross-sectional, although new-onset diabetes was assessed after chemotherapy initiation. The study protocol was approved by the Ethics Committee of Tokyo University of Pharmacy and Life Sciences (approval number: 2025-033). This study followed the Reporting of Studies Conducted Using Observational Routinely Collected Health Data for Pharmacoepidemiology (RECORD-PE) statement.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eEligibility criteria included patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years with solid tumors who received parenteral anticancer agents along with dexamethasone. These anticancer agents were identified using Anatomical Therapeutic Chemical (ATC) code L and were individually reviewed to ensure clinical relevance. The index month was defined as the first month in which a patient received these anticancer agents within the database between April 2014 and March 2023. We adopted a new-user design with a 6-month washout period to eliminate prevalent user bias. Exclusion criteria were: (1) diabetes during the index month or in the 6 months prior, (2) hematologic malignancy during the index month, and (3) no dexamethasone administration during the 3 months after the index month. Diabetes was defined using International Classification of Diseases 10th Revision (ICD-10) codes (E10.x\u0026ndash;E14.x) or prescription data (ATC code A10). Hematologic malignancy was defined using ICD-10 codes for malignant neoplasms (C81.x\u0026ndash;C96.x).\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was new-onset diabetes during the 2 months following the index month. Based on a previous validation study [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], new-onset diabetes was defined using ICD-10 codes (E11.x\u0026ndash;E14.x) excluding type 1 diabetes, or prescription data (ATC code A10). To exclude prevalent cases, patients with diabetes diagnosis during the index month were excluded. Accordingly, incidence was evaluated over the subsequent two months (month 1 and month 2). The assessment period of 3 months was defined based on a previous study [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Secondary outcomes included the frequency and timing of new-onset diabetes.\u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cp\u003eVariables that could potentially affect the outcome were selected. Age was categorized as \u0026lt;\u0026thinsp;70 or \u0026ge;\u0026thinsp;70 years at the index month. Sex was classified as male or female. Comorbidities, including hypertension, hyperuricemia, dyslipidemia, depression, and insomnia, were defined using ICD-10 codes during the index month or in the 6 months prior (Online Resource 1). Pancreatic cancer was identified using ICD-10 codes (C25.x) during the index month to define the population initiating chemotherapy. The Charlson Comorbidity Index (CCI) was calculated based on a previously validated study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], using ICD-10 codes recorded during the index month or in the 6 months prior (Online Resource 2). NK1-RAs, including aprepitant, fosaprepitant, and fosnetupitant, were identified using ATC code A04AD. Concomitant medications included olanzapine and systemic steroids other than dexamethasone, identified using ATC codes (N05AH03; H02AB excluding H02AB02 [dexamethasone] and H02AB08 [triamcinolone]) during the index month and the subsequent 2 months. Dexamethasone was identified using ATC code H02AB02, and the total dose during the index month and subsequent 2 months was calculated. Surgery was defined using treatment codes for general anesthesia and endotracheal intubation recorded during the index month or in the 6 months prior.\u003c/p\u003e \u003cp\u003eMost variables were selected based on previous studies [\u003cspan additionalcitationids=\"CR24 CR25 CR26\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], while others were chosen based on clinical relevance. Specifically, the CCI score was included as a validated measure of overall comorbidity burden. Olanzapine was included as an exploratory variable because its use is contraindicated in patients with diabetes in Japan and may influence both prescribing patterns and diabetes risk.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized using the mean and standard deviation. Categorical variables were summarized as frequencies and percentages. Missing data were not imputed because the study relied on claims-based diagnostic and procedural codes, for which the absence of a code was assumed to indicate the absence of the condition or treatment. For the primary analysis, multivariable logistic regression was used to assess the association between NK1-RA administration along with dexamethasone and new-onset diabetes. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values were calculated for each variable. New-onset diabetes was defined as the dependent variable, and the covariates described above were included as independent variables. Sensitivity analyses were conducted by (1) restricting the outcome definition to both ICD-10 codes and prescription data to increase diagnostic specificity, (2) extending the assessment period to 6 months, and (3) excluding covariates with high ORs. Due to the exploratory nature of this study, a sample size calculation was not performed. A two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were performed using R software, version 4.5.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eParticipants flow and characteristics\u003c/h2\u003e \u003cp\u003eThe participant flow is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. During the enrollment period, 252,056 patients were initially identified. Of these, 180,517 patients were excluded: 74,391 were excluded due to an insufficient look-back period; 78,571 had a history of diabetes; 8,067 had hematologic malignancies; and 19,488 had not received dexamethasone. Consequently, 71,539 patients were included in the analysis. Patient characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. During the 3-month assessment period, the mean duration of chemotherapy was 2.51 months. NK1-RAs were administered to 51.1% of patients, with a mean duration of 2.32 months.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge (years), mean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;71,539\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.6 (10.6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male / female), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36,332 (50.8) / 35,207 (49.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33,735 (47.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperuricemia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,443 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22,173 (31.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3731 (5.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19,193 (26.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic cancer, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,796 (6.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI score without cancer\u0026thinsp;\u0026ge;\u0026thinsp;1, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46967 (65.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcomitant medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNK1-RA, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36,583 (51.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlanzapine, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,841 (6.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal dose of dexamethasone, mg mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.2 (35.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSteroid except dexamethasone, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9,928 (13.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery before chemotherapy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25,489 (35.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eCCI\u003c/em\u003e Charlson comorbidity index, \u003cem\u003eNK1-RA\u003c/em\u003e neurokinin 1 receptor antagonist, \u003cem\u003eSD\u003c/em\u003e standard deviation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrimary outcome\u003c/h3\u003e\n\u003cp\u003eThe association between NK1-RA administration along with dexamethasone and new-onset diabetes is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. NK1-RA administration was significantly associated with new-onset diabetes (OR: 1.43; 95% CI: 1.31\u0026ndash;1.55).\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\u003eMultivariable logistic regression analysis for new-onset diabetes\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% confidence interval\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.98\u0026ndash;1.16\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.63\u0026ndash;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.13\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperuricemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026ndash;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsomnia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026ndash;1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.77\u0026ndash;4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI score without cancer\u0026thinsp;\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05\u0026ndash;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNK1-RA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.31\u0026ndash;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlanzapine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal dose of dexamethasone\u0026thinsp;\u0026ge;\u0026thinsp;50 mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026ndash;1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSteroid except dexamethasone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.79\u0026ndash;3.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgery before chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u0026ndash;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eCCI\u003c/em\u003e Charlson comorbidity index, \u003cem\u003eNK1-RA\u003c/em\u003e neurokinin 1 receptor antagonist.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOther factors significantly associated with new-onset diabetes included age\u0026thinsp;\u0026ge;\u0026thinsp;70 years, hypertension, dyslipidemia, pancreatic cancer, a CCI score excluding cancer\u0026thinsp;\u0026ge;\u0026thinsp;1, a total dexamethasone dose\u0026thinsp;\u0026ge;\u0026thinsp;50 mg, and the use of systemic steroids other than dexamethasone. In contrast, female sex and prior surgery were significantly associated with a decreased risk of new-onset diabetes.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSecondary outcomes\u003c/h2\u003e \u003cp\u003eRegarding the frequency and timing of new-onset diabetes, 2,826 patients (4.0%) developed diabetes during the assessment period. Of these, 1,366 cases occurred in the month following the index month (month 1), and 1,460 cases occurred in the subsequent month (month 2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eFour sensitivity analyses were conducted. When the definition of new-onset diabetes was narrowed to cases identified by both ICD-10 codes and prescription data, NK1-RA administration remained significantly associated with new-onset diabetes (OR: 1.36; 95% CI: 1.13\u0026ndash;1.64; Online Resource 3). Similarly, significant associations were observed when the assessment period was extended to 6 months (OR: 1.37; 95% CI: 1.29\u0026ndash;1.46; Online Resource 4) and when covariates with high ORs, including pancreatic cancer or systemic steroids other than dexamethasone, were excluded (OR: 1.14; 95% CI: 1.05\u0026ndash;1.23, and OR: 1.45; 95% CI: 1.28\u0026ndash;1.51, respectively; Online Resources 5 and 6).\u003c/p\u003e \u003cp\u003eAcross all sensitivity analyses, pancreatic cancer, systemic steroids other than dexamethasone, and the CCI score remained consistently associated with new-onset diabetes, while female sex and prior surgery remained significantly associated with a decreased risk (Online Resources 3\u0026ndash;6).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings suggest that NK1-RA administration along with dexamethasone for CINV is associated with an increased risk of new-onset diabetes, and this demonstrated high robustness across multiple sensitivity analyses. To our knowledge, this study is the first to investigate the association between NK1-RA administration along with dexamethasone for CINV and new-onset diabetes. These findings highlight a previously unrecognized safety signal associated with NK1-RAs and may provide an opportunity to reconsider and optimize antiemetic strategies.\u003c/p\u003e \u003cp\u003eThe cross-sectional design limits causal inference; however, several considerations support the plausibility of the observed association. Previous studies have identified several risk factors for CINV; however, diabetes has not been reported as one of them [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, current clinical guidelines do not recommend prioritizing NK1-RA administration or intensifying antiemetic therapy specifically for patients with diabetes [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, baseline selection bias is unlikely. In addition, among patients receiving NK1-RAs, the duration of administration accounted for most of the 3-month assessment period, further supporting the observed association between NK1-RA administration and new-onset diabetes.\u003c/p\u003e \u003cp\u003eThe frequency of diabetes during HEC (57.1%) and moderately emetogenic chemotherapy (42.9%) has been reported in a previous study [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In that study, 14.3% of patients with cancer and no history of diabetes developed diabetes within 3 months after starting chemotherapy. Furthermore, 50.6% of patients developed insulin resistance, compared with 28.6% at baseline. These rates are higher than those observed in our study (4.0%), likely because of differences in data collection methods.\u003c/p\u003e \u003cp\u003eWe relied on health claims data, whereas the previous study used blood test data, such as homeostasis model assessment of insulin resistance, fasting plasma glucose, 2-h postprandial glucose, and hemoglobin A1c. Therefore, if laboratory data had been available in our analysis, additional cases of new-onset diabetes might have been identified, potentially resulting in a higher OR. However, this possibility remains unclear.\u003c/p\u003e \u003cp\u003eOur proposed mechanism is that the DDI between NK1-RAs and dexamethasone increases dexamethasone concentrations. Co-administration of NK1-RAs has been reported to double the area under the concentration\u0026ndash;time curve of dexamethasone through inhibition of CYP3A4 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. As noted earlier, dexamethasone used as an antiemetic drug during chemotherapy can lead to the development of diabetes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, increased dexamethasone exposure may facilitate the development of diabetes as an adverse effect. This pharmacokinetic interaction may have contributed to the association observed in our study. In basic research, the NK1 receptor and its ligand, substance P, are involved in blood glucose regulation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, the underlying mechanisms are complex and remain controversial. Some studies suggest that NK1-RAs may prevent diabetes [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], while others report a potential increase in risk [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Therefore, the direct effect of NK1-RAs on glucose metabolism remains unclear. Taken together, the DDI between NK1-RAs and dexamethasone is a plausible mechanism for new-onset diabetes.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, because of the nature of health claims data, we could not adjust for important variables such as body mass index, diet, exercise habits, and family history of diabetes. Second, the use of a washout period to define new users may have reduced the number of patients aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years, when many patients transition to the Medical Care System for the Advanced Elderly. This might have resulted in slight differences between our study population and the general age distribution.\u003c/p\u003e \u003cp\u003eIn conclusion, we suggest an association between NK1-RA administration along with dexamethasone for CINV and new-onset diabetes. This finding provides an opportunity to further optimize antiemetic therapies, such as sparing NK1-RAs or reducing the dexamethasone dose to mitigate unnecessary steroid potentiation. Given the potential clinical implications for antiemetic decision-making, future research is needed to clarify causality using alternative study designs, such as cohort studies, as well as to identify patient populations at high risk for developing diabetes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYO is the principal investigator. YO and SS contributed to the conception of the study. YO, SS, TK and SI designed the study. YO, SS, TK, TY, TI, KS, YH and SI performed data interpretation. YO, SS and TK contributed to data management and statistical analysis. YO drafted the original manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no conflicts of interest related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the ethics committee of Tokyo University of Pharmacy and Life Sciences (approval number: 2025-033).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable due to the use of anonymized health claims data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Editage (www.editage.com) for English language editing.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlaus A, Knipping C, Morant R, et al (2004) Chemotherapy-induced nausea and vomiting in routine practice: A European perspective. 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Front Neurosci 12:806. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fnins.2018.00806\u003c/span\u003e\u003cspan address=\"10.3389/fnins.2018.00806\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"neurokinin-1 receptor antagonist, dexamethasone, diabetes, drug-drug interaction, chemotherapy","lastPublishedDoi":"10.21203/rs.3.rs-9079117/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9079117/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eWe aimed to optimize antiemetic strategies by evaluating the impact of neurokinin-1 receptor antagonist (NK1-RA) administration along with dexamethasone on new-onset diabetes in patients receiving chemotherapy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cross-sectional study was conducted using the DeSC database and included patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years with solid tumors who initiated parenteral anticancer agents and dexamethasone between April 2014 and March 2023. Patients with a history of diabetes or hematologic malignancies were excluded. The primary outcome was new-onset diabetes during the 2 months following the index month, defined by International Classification of Diseases, Tenth Revision codes or prescription data. Multivariable logistic regression assessed the association between NK1-RA administration along with dexamethasone and new-onset diabetes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 71,539 eligible patients, 51.1% received NK1-RAs. NK1-RA administration along with dexamethasone was significantly associated with an increased risk of new-onset diabetes (adjusted odds ratio: 1.43; 95% confidence interval: 1.31\u0026ndash;1.55; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Sensitivity analyses demonstrated consistent results across different evaluation periods and outcome definitions.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eNK1-RA administration along with dexamethasone was associated with an increased risk of new-onset diabetes, likely due to a drug\u0026ndash;drug interaction that increases dexamethasone concentrations. These findings suggest the need to optimize antiemetic strategies, including sparing NK1-RAs or reducing the dexamethasone dose to minimize unnecessary steroid potentiation.\u003c/p\u003e","manuscriptTitle":"Impact of Neurokinin-1 Receptor Antagonists on New-Onset Diabetes in Patients Receiving Chemotherapy: A Retrospective Cross-Sectional Study Using Health Claims Database in Japan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 07:04:46","doi":"10.21203/rs.3.rs-9079117/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"105740792096715177869566759796638980659","date":"2026-04-28T07:18:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T07:04:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-11T17:56:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-17T11:52:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2026-03-10T04:43:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1cd8fdb1-582a-4cbd-a906-ea4de33dea82","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T07:04:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 07:04:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9079117","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9079117","identity":"rs-9079117","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}