論文 - 長島　健悟

Recurrence-free survival as a surrogate endpoint for overall survival after neoadjuvant chemotherapy and surgery for oesophageal squamous cell carcinoma

Okui J*, Nagashima K*, Matsuda S*, Sato Y, Okamura A, Kawakubo H, Muto M, Kakeji Y, Kono K, Takeuchi H, Watanabe M, Doki Y, Bamba T, Fukuda T, Fujiwara H, Sato S, Noma K, Miyata H, Fujita T, Kitagawa Y

British Journal of Surgery 111 （ 2 ） znae038 2024年02月

共著, 筆頭著者, 査読有り,  ISSN  00071323

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Bias in odds ratios from logistic regression methods with sparse data sets

Masahiko Gosho, Tomohiro Ohigashi, Kengo Nagashima, Yuri Ito, Kazushi Maruo

Journal of Epidemiology 33 （ 6 ） 265 - 275 2023年06月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0917-5040

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Sample size calculations for single‐arm survival studies using transformations of the Kaplan–Meier estimator

Nagashima K, Noma H, Sato Y, Gosho M

Pharmaceutical Statistics 20 （ 3 ） 499 - 511 2021年05月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  15391604

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Prediction intervals for random-effects meta-analysis: a confidence distribution approach

Nagashima K, Noma H, Furukawa TA

Statistical Methods in Medical Research 28 （ 6 ） 1689 - 1702 2019年06月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  09622802

　概要を見る

Prediction intervals are commonly used in meta-analysis with random-effects models. One widely used method, the Higgins–Thompson–Spiegelhalter prediction interval, replaces the heterogeneity parameter with its point estimate, but its validity strongly depends on a large sample approximation. This is a weakness in meta-analyses with few studies. We propose an alternative based on bootstrap and show by simulations that its coverage is close to the nominal level, unlike the Higgins–Thompson–Spiegelhalter method and its extensions. The proposed method was applied in three meta-analyses.

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Information criteria for Firth's penalized partial likelihood approach in Cox regression models

Nagashima K, Sato Y

Statistics in Medicine 36 （ 21 ） 3422 - 3436 2017年09月

研究論文（学術雑誌）, 共著, 査読有り

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Statistical methods in the Journal — an update

Sato Y, Gosho M, Nagashima K, Takahashi S, Ware JH, Laird NM

New England Journal of Medicine 376 （ 11 ） 1086 - 1087 2017年03月

研究論文（学術雑誌）, 共著, 査読有り

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An efficient and robust method for analyzing population pharmacokinetic data in genome-wide pharmacogenomic studies: a generalized estimating equation approach

Nagashima K, Sato Y, Noma H, Hamada C

Statistics in Medicine 32 （ 27 ） 4838 - 4858 2013年11月

研究論文（学術雑誌）, 査読有り

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Meta-analysis using flexible random-effects distribution models

Noma H, Nagashima K, Kato S, Teramukai S, Furukawa TA

Journal of Epidemiology 32 （ 10 ） 441 - 448 2022年10月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0917-5040

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Frequentist performances of Bayesian prediction intervals for random‐effects meta‐analysis

Hamaguchi Y, Noma H, Nagashima K, Yamada T, Furukawa TA

Biometrical Journal 63 （ 2 ） 394 - 405 2021年02月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  03233847

　概要を見る

The prediction interval has been increasingly used in meta-analyses as a useful measure for assessing the magnitude of treatment effect and between-studies heterogeneity. In calculations of the prediction interval, although the Higgins–Thompson–Spiegelhalter method is used most often in practice, it might not have adequate coverage probability for the true treatment effect of a future study under realistic situations. An effective alternative candidate is the Bayesian prediction interval, which has also been widely used in general prediction problems. However, these prediction intervals are constructed based on the Bayesian philosophy, and their frequentist validities are only justified by large-sample approximations even if noninformative priors are adopted. There has been no certain evidence that evaluated their frequentist performances under realistic situations of meta-analyses. In this study, we conducted extensive simulation studies to assess the frequentist coverage performances of Bayesian prediction intervals with 11 noninformative prior distributions under general meta-analysis settings. Through these simulation studies, we found that frequentist coverage performances strongly depended on what prior distributions were adopted. In addition, when the number of studies was smaller than 10, there were no prior distributions that retained accurate frequentist coverage properties. We also illustrated these methods via applications to two real meta-analysis datasets. The resultant prediction intervals also differed according to the adopted prior distributions. Inaccurate prediction intervals may provide invalid evidence and misleading conclusions. Thus, if frequentist accuracy is required, Bayesian prediction intervals should be used cautiously in practice.

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Permutation inference methods for multivariate meta‐analysis

Noma H, Nagashima K, Furukawa TA

Biometrics 76 （ 1 ） 337 - 347 2020年03月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0006341X

　概要を見る

Multivariate meta-analysis is gaining prominence in evidence synthesis research because it enables simultaneous synthesis of multiple correlated outcome data, and random-effects models have generally been used for addressing between-studies heterogeneities. However, coverage probabilities of confidence regions or intervals for standard inference methods for random-effects models (eg, restricted maximum likelihood estimation) cannot retain their nominal confidence levels in general, especially when the number of synthesized studies is small because their validities depend on large sample approximations. In this article, we provide permutation-based inference methods that enable exact joint inferences for average outcome measures without large sample approximations. We also provide accurate marginal inference methods under general settings of multivariate meta-analyses. We propose effective approaches for permutation inferences using optimal weighting based on the efficient score statistic. The effectiveness of the proposed methods is illustrated via applications to bivariate meta-analyses of diagnostic accuracy studies for airway eosinophilia in asthma and a network meta-analysis for antihypertensive drugs on incident diabetes, as well as through simulation experiments. In numerical evaluations performed via simulations, our methods generally provided accurate confidence regions or intervals under a broad range of settings, whereas the current standard inference methods exhibited serious undercoverage properties.

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Bartlett‐type corrections and bootstrap adjustments of likelihood‐based inference methods for network meta‐analysis

Noma H, Nagashima K, Maruo K, Gosho M, Furukawa TA

Statistics in Medicine 37 （ 7 ） 1178 - 1190 2018年03月

研究論文（学術雑誌）, 共著, 査読有り

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A note on the Mantel–Haenszel estimators when the common effect assumptions are violated

Noma H, Nagashima K

Epidemiologic Methods 5 （ 1 ） 19 - 35 2016年05月

研究論文（学術雑誌）, 共著, 査読有り

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Impact of the COVID‐19 pandemic on gastric surgery in Japan: A nationwide study using interrupted time‐series analyses

Fujita M, Yamaguchi K, Nagashima K, Suzuki K, Kasai T, Hashimoto H, Onouchi Y, Sato D, Fujisawa T, Hata A

Journal of Gastroenterology and Hepatology    In press 2024年

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0815-9319

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Risk factors for recurrence in patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative early breast cancer in Japan: a systematic literature review and meta-analysis

Miyazaki N, Iwasaki T, Sakai H, Watanuki R, Tanizawa Y, Cai Z, Kawaguchi T, Tsurutani J, Nagashima K

Current Medical Research and Opinion    In press 2024年

研究論文（学術雑誌）, 共著, 責任著者, 査読有り

Prevalence and clinical profiles of anti‐myelin‐associated glycoprotein neuropathy in Japan: A nationwide survey study of 133 patients

Aotsuka Y, Misawa S, Suichi T, Shibuya K, Nakamura K, Kano H, Otani R, Marie M, Ogushi M, Nagashima K, Sato Y, Kuriyama N, Kuwabara S

European Journal of Neurology 31 （ 5 ） e16249 2024年05月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  1351-5101

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Live two-way video versus face-to-face treatment for depression, anxiety, and obsessive-compulsive disorder: A 24-week randomized controlled trial

Kishimoto T, Kinoshita S, Kitazawa M, Hishimoto A, Asami T, Suda A, Bun S, Kikuchi T, Sado M, Takamiya A, Mimura M, Sato Y, Takemura R, Nagashima K, Nakamae T, Abe Y, Kanazawa T, Kawabata Y, Tomita H, Abe K, Hongo S, Kimura H, Sato A, Kida H, Sakuma K, Funayama M, Sugiyama N, Hino K, Amagai T, Takamiya M, Kodama H, Goto K, Fujiwara S, Kaiya H, Nagao K, on behalf of the J-PROTECT collaborators

Psychiatry and Clinical Neurosciences 78 （ 4 ） 220 - 228 2024年04月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  1323-1316

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Factors affecting motivation for receiving a booster dose of the COVID-19 vaccine among Japanese university students and staff: a cross-sectional questionnaire survey

Uchida S, Uno S, Kondo M, Uwamino Y, Namkoong H, Nishimura T, Misawa K, Kashimura S, Yamato K, Ishizaka T, Nagashima K, Kitagawa Y, Hasegawa N

Scientific Reports 14 （ 1 ） 8009 2024年04月

研究論文（学術雑誌）, 共著, 査読有り

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Predictive and prognostic value of excision repair cross-complementing group 1 in patients with advanced gastric cancer

Yamada Y, Nagashima K, Azuma M, Masutani M, Ichikawa H, Iwasa S, Takahashi N, Hirano H, Kanato K, Machida N, Kinoshita T, Hata H, Kawakami H, Takahari D, Boku N, Kurokawa Y, Terashima M, Yoshikawa T, Sekine S, Hiraoka N

BJC Reports 2   18 2024年03月

研究論文（学術雑誌）, 共著, 査読有り

Clinical development of a blood biomarker using apolipoprotein-A2 isoforms for early detection of pancreatic cancer

Kashiro A, Kobayashi M, Oh T, Miyamoto M, Atsumi J, Nagashima K, Takeuchi K, Nara S, Hijioka S, Morizane C, Kikuchi S, Kato S, Kato K, Ochiai H, Obata D, Shizume Y, Konishi H, Nomura Y, Matsuyama K, Xie C, Wong C, Huang Y, Jung G, Srivastava S, Kutsumi H, Honda K

Journal of Gastroenterology 59 （ 3 ） 263 - 278 2024年03月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0944-1174

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Prevalence, clinical profiles, and prognosis of CIDP in Japanese nationwide survey: analyses of 1257 diagnosis-confirmed patients

Aotsuka Y, Misawa S, Suichi T, Shibuya K, Nakamura K, Kano H, Otani R, Morooka M, Ogushi M, Nagashima K, Sato Y, Kuriyama N, Kuwabara S

Neurology 102 （ 6 ） e209130 2024年03月

研究論文（学術雑誌）, 共著, 査読有り,  ISSN  0028-3878

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