Research

日本語

Please see my Google Scholar page for a full list of publications. Here, I highlight research focusing on methodological developments in biostatistics.

Accepted / Published Papers

[9] Kojima, M., Yamada, K., Sunami, H., Takeda, K., & Hanada, K. (2026). Hybrid Non‐Informative and Informative Prior Model‐Assisted Designs for Mid‐Trial Dose Insertion. Statistics in Medicine, 45(20-22). [paper, DOI, arXiv]

[8] Hanada, K., & Kojima, M. (2026). Integrating Meta‐Analysis Into a Specific Study (InMASS) for Estimating the Target‐Population Average Treatment Effect. Biometrical Journal, 68(5). [paper, DOI, arXiv]

We propose a method that uses meta-analysis to estimate the average treatment effect in a target population represented by a specific study.

[7] Hanada, K., & Sugimoto, T. (2026). Random-effects meta-analysis via generalized linear mixed models: A Bartlett-corrected approach for few studies. Biometrics, 82(3), ujag148. [paper, DOI, arXiv, GitHub]

We develop random-effects meta-analysis under generalized linear mixed models and propose a simple Bartlett correction that gives accurate interval estimation with few studies.

[6] Hanada, K., & Kojima, M. (2026). Random Effect Restricted Mean Survival Time Model. Journal of Biopharmaceutical Statistics, 1-16. [paper, DOI, arXiv]

We introduce random effects into RMST regression, enabling cluster-specific shrinkage estimates based on the overall effect.

[5] Kojima, M., Orihara, S., Hanada, K., & Ohigashi, T. (2026). Sample size re-estimation in blinded hybrid-control design using inverse probability weighting. Statistics in Medicine, 45(3-5), e70429. [paper, DOI, arXiv]

[4] Kojima, M., Mano, H., Yamada, K., Hanada, K., Tanaka, Y., & Moriya, J. (2025). Adjusting confidence intervals under covariate-adaptive randomization in non-inferiority and equivalence trials. Contemporary Clinical Trials, 158, 108099. [paper, arXiv]

We propose confidence-interval adjustments for non-inferiority and equivalence testing under rerandomization and covariate-adaptive randomization.

[3] Hanada, K., & Sugimoto, T. (2024). Meta-Analysis for Time-to-event Outcome Based on Restored Individual Participant Data and Summary Statistics. Japanese Journal of Biometrics, 45(1), 115-131 (in Japanese). [paper, arXiv]

We compare reconstructed individual-participant-data meta-analysis with summary-statistics approaches for time-to-event outcomes through simulation.

[2] Hanada, K., Moriya, J., & Kojima, M. (2024). Comparison of baseline covariate adjustment methods for restricted mean survival time. Contemporary Clinical Trials, 138, 107440. [paper]

We compare model-based RMST analyses by simulation and identify when different adjustment methods are appropriate.

[1] Hanada, K., & Sugimoto, T. (2023). Inference using an exact distribution of test statistic for random-effects meta-analysis. Annals of the Institute of Statistical Mathematics, 75(2), 281-302. [paper, DOI]

We derive an exact distribution for a test statistic in random-effects meta-analysis and study its use for testing and interval estimation.

Medical Research

[7] Hirano, S., Hanada, K., & Maeda, H. (2026). Race and trial region changes in cancer clinical trials between 2013 and 2024. Frontiers in Medicine, 13, 1894533. [paper, DOI]

We examined changes in racial representation and trial regions in cancer clinical trials supporting FDA drug approvals between 2013 and 2024.

[6] Tamura, T., Matsumori, T., Nishikawa, Y., Kitagawa, K., Nagai, M., Shimizu, A., Matsumoto, I., Masuda, A., Sakai, A., Yamai, T., Tomokuni, A., Ikeura, T., Ito, T., Doi, T., Miyake, H., Maruyama, H., Ishikawa-Kakiya, Y., Ogura, T., Ueno, S., Shiomi, H., Tsujimoto, A., Shintani, S., Ikeda, T., Uenoyama, Y., Emori, T., Shimatani, M., Hanada, K., Kitano, M., & Takenaka, M. (2026). Impact of Stent Type on Surgical Outcomes in Pancreatic Cancer Patients Undergoing Preoperative Biliary Drainage. Digestive Endoscopy, 38(7). [paper, DOI]

This multicentre retrospective study compared metal and plastic stents for preoperative biliary drainage in patients with pancreatic ductal adenocarcinoma receiving neoadjuvant treatment.

[5] Sagan, K., Kojima, F., Matsuzaki, I., Hanada, K., Musangile, F. Y., Nakamoto, T., Hayashi, H., Ohe, C., Ohashi, R., Nagashima, Y., Kohjimoto, Y., & Murata, S. I. (2026). Clear Cell Papillary Renal Cell Tumor Revisited: Comparison of Histologic and Immunohistochemical Profiles in Relation to VHL Allelic Status. The American Journal of Surgical Pathology.

[4] Nakayama, Y., Kume, K., Baba, T., Ayaki, T., Hanada, K., Miyamoto, K., Inoue, N., Kawakami, H., & Ito, H. (2026). Neuropathological and Molecular Features Associated With a Heterozygous DNAJC7 Mutation in Amyotrophic Lateral Sclerosis. Neuropathology and Applied Neurobiology, 52(4), e70086.

[3] Kitadani, J., Hayata, K., Goda, T., Tominaga, S., Fukuda, N., Nakai, T., Nagano, S., Hanada, K., & Kawai, M. (2026). Impact of intraoperative nerve integrity monitoring on recurrent laryngeal nerve paralysis in minimally invasive esophagectomy for esophageal cancer: a propensity score-matched analysis. Surgical Endoscopy, 1-10.

[2] Itonaga, M., Ashida, R., Tamura, T., Yamashita, Y., Kawaji, Y., Shishimoto, T., Morishita, M., Hanada, K., Kojima, F., & Kitano, M. (2026). Comparison of Nanoliposomal Irinotecan Plus Fluorouracil/Leucovorin and S-1, Irinotecan, and Oxaliplatin as Second-Line Chemotherapy After Gemcitabine Plus Nab-Paclitaxel for Unresectable Pancreatic Cancer. Journal of Hepato-Biliary-Pancreatic Sciences, 1-11.

[1] Hirano, S., Hanada, K., & Maeda, H. (2025). Potential surrogate endpoint for B-cell hematologic malignancy: A systematic review and meta-analysis. Scientific Reports, 15, 19300. [paper]

Preprints / Submitted Manuscripts

[4] Hanada, K., & Kojima, M. (2026). Covariate-Adaptive Sample Size Re-estimation for Population-Standardized Historical Control Designs in Single-Arm Trials. arXiv preprint arXiv:2607.25159, submitted. [arXiv]

We propose covariate-adjusted sample-size planning and re-estimation for single-arm trials using population-standardized historical controls.

[3] Hanada, K., Shimokawa, T., & Maruo, K. (2026). Differentially Private One-Shot Federated Inference for Linear Mixed Models via Lossless Likelihood Reconstruction. arXiv preprint arXiv:2604.00410, submitted. [arXiv]

We propose differentially private linear mixed-model inference based only on facility-level summaries and study the privacy-accuracy tradeoff.

[2] Kojima, M., Hanada, K., & Sato, A. (2025). A Clustering Approach for Basket Trials Based on Treatment Response Trajectories. arXiv preprint arXiv:2511.09890, submitted. [arXiv]

[1] Hanada, K., & Kojima, M. (2024). Bayesian Parametric Methods for Deriving Distribution of Restricted Mean Survival Time. arXiv preprint arXiv:2406.06071, submitted. [arXiv]

We formulate RMST under parametric survival models, add random and frailty effects, and propose Bayesian inference with consistency properties.

Conference Presentations (International)

[5] Hanada, K., Shimokawa, T., & Maruo, K. (2026). Privacy-Preserving One-Shot Federated Inference for Linear Mixed Models. 33rd International Biometric Conference, Seoul. [event]

[4] Hanada, K. (2026). Random-effects meta-analysis via generalized linear mixed models: A Bartlett-corrected approach for few studies. Recent Advances in Meta-Analysis 2026, Göttingen. [event]

[3] Hanada, K., & Sugimoto, T. (2025). Random-effects meta-analysis via generalized linear mixed models for few studies. The 13th Conference of the IASC-ARS, Ho Chi Minh City. [oral]

[2] Hanada, K., & Kojima, M. (2025). Integrate Meta-analysis into Specific Study for Estimating Conditional Average Treatment Effect. Joint Statistical Meetings 2025, Nashville. [poster]

[1] Hanada, K., & Sugimoto, T. (2019). Non-Asymptotic Properties and Behaviors for Random-Effects Meta-Analysis When the Number of Studies Is Small. The VI-th International Symposium on Biopharmaceutical Statistics, Kyoto.

Conference Presentations (JPN Domestic)

[16] Hanada, K. (2026). Meta-Analysis of Survival Functions Based on Kaplan-Meier Curves with Limited Risk Set Information. Japanese Joint Statistical Meeting 2026. [event]

[15] Hanada, K. (2026). Survival Meta-Analysis by Integrating Kaplan-Meier Curves. 40th Annual Meeting of the Japanese Society of Computational Statistics. [event]

[14] Hanada, K., Shimokawa, T., & Maruo, K. (2026). Lossless One-Shot Federated Learning and Privacy Protection for Linear Mixed Models. 2026 Annual Meeting of the Biometric Society of Japan. [event]

[13] Hanada, K. (2026). Differentially private distributed regression analysis for linear mixed models. The 73rd Oita Statistical Meeting. [event]

[12] Hanada, K., & Sugimoto, T. (2025). Inference for Generalized Linear Random-Effects Meta-Analysis with Few Studies. KAKENHI Symposium: Comprehensive Exploration of Cross-Disciplinary Foundations and Practices in Data Science. [oral]

[11] Hanada, K. (2025). Generalized Linear Random-Effects Meta-Analysis with Few Studies. 2025 Japanese Joint Statistical Meeting.

[10] Hanada, K., & Kojima, M. (2025). Use of Meta-Analysis for Treatment Effect Estimation in Clinical Trials. 2025 Annual Meeting of the Biometric Society of Japan.

[9] Hanada, K., & Sugimoto, T. (2024). Joint Distribution of the Average Treatment Effect and Between-Study Variance in Meta-Analysis and Its Application. 7th Kagoshima Data Science Symposium.

[8] Hanada, K., & Kojima, M. (2024). Random Effect Restricted Mean Survival Time Model. 2024 Japanese Joint Statistical Meeting.

[7] Hanada, K., & Sugimoto, T. (2024). Variance Estimation in Meta-Analysis with Few Studies. 38th Annual Meeting of the Japanese Society of Computational Statistics.

[6] Hanada, K., & Sugimoto, T. (2023). Individual Participant Data Reconstruction and Meta-Analysis for Time-to-Event Outcomes. 5th Kagoshima Data Science Symposium.

[5] Hanada, K., Moriya, J., & Kojima, M. (2023). Comparison of Covariate Adjustment Methods for Restricted Mean Survival Time (RMST). 2023 Japanese Joint Statistical Meeting.

[4] Hanada, K. (2022). Inference for Binary Meta-Analysis with Few Events. 3rd Kagoshima Data Science Symposium.

[3] Hanada, K., & Sugimoto, T. (2019). Non-Asymptotic Properties of Random-Effects Meta-Analysis with Few Studies. 33rd Symposium of the Japanese Society of Computational Statistics.

[2] Hanada, K., & Sugimoto, T. (2018). Sampling Distribution in Random-Effects DerSimonian-Laird Stratified Analysis. 32nd Symposium of the Japanese Society of Computational Statistics.

[1] Hanada, K., & Sugimoto, T. (2018). Sampling Distribution in Random-Effects Stratified Analysis for Normal Populations. 57th Oita Statistical Meeting.

Other Research Outputs

[1] Hanada, K. (2024). Inference and Exact Distributions for Random-Effects Meta-Analysis. Doctoral dissertation, Shiga University. [paper]

My doctoral dissertation studies meta-analysis with few studies and reconstructed individual-participant-data meta-analysis for time-to-event outcomes.

Software

[2] Hanada, K. (2024). rmstBayespara. R package: Bayesian Restricted Mean Survival Time for Cluster Effect. [CRAN]

[1] Hanada, K. (2024). aedl. R package: Almost-Exact Inference for the DerSimonian-Laird Test Statistic. [CRAN]

Other information is available on researchmap.