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大学・研究所にある論文を検索できる 「Real-World Outcomes of Systemic Therapy in Japanese Patients with Cancer (Tokushukai REAl-World Data Project: TREAD): Study Protocol for a Nationwide Cohort Study」の論文概要。リケラボ論文検索は、全国の大学リポジトリにある学位論文・教授論文を一括検索できる論文検索サービスです。

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Real-World Outcomes of Systemic Therapy in Japanese Patients with Cancer (Tokushukai REAl-World Data Project: TREAD): Study Protocol for a Nationwide Cohort Study

Shimoyama, Rai Imamura, Yoshinori Uryu, Kiyoaki Mase, Takahiro Fujimura, Yoshiaki Hayashi, Maki Ohtaki, Megu Ohtani, Keiko Shinozaki, Nobuaki Minami, Hironobu 神戸大学

2022.11

概要

Cohort studies using large-scale databases have become increasingly important in recent years. The Tokushukai Medical Group is a leading medical group in Japan that includes 71 general hospitals nationwide from Hokkaido to Okinawa, with a total of 18,000 beds, and a unified electronic medical record system. This retrospective cohort study aims to evaluate the real-world outcomes of systemic therapy for Japanese patients with cancer using this merit of scale. All adult patients with cancer who received systemic therapy using a centrally registered chemotherapy protocol system at 46 hospitals from April 2010 to March 2020 will be identified (~48,850 patients). Key exclusion criteria include active double cancer and inadequate data extraction. Data will be obtained through electronic medical records, diagnosis procedure combination data, medical prescription data, and the national cancer registration system that includes sociodemographic variables, diagnostic and laboratory tests, concomitant drug prescriptions, cost, and overall survival. Kaplan–Meier estimates will be calculated for time-to-event analyses. Stratified/conventional Cox proportional hazards regression analyses will be conducted to examine the relationships between overall survival and related factors. Our findings provide important insights for future research directions, policy initiatives, medical guidelines, and clinical decision-making.

参考文献

1. Streptomycin in Tuberculosis Trials Committee. Streptomycin treatment of pulmonary tuberculosis. Br. Med. J. 1948, 2, 769–782. [CrossRef]

2. Bothwell, L.E.; Podolsky, S.H. The emergence of the randomized, controlled trial. N. Engl. J. Med. 2016, 375, 501–504. [CrossRef] [PubMed]

3. Milsted, R. Cancer drug approval in the United States, Europe, and Japan. Adv. Cancer Res. 2006, 96, 371–391. [CrossRef]

4. Townsley, C.A.; Selby, R.; Siu, L.L. Systematic review of barriers to the recruitment of older patients with cancer onto clinical trials. J. Clin. Oncol. 2005, 23, 3112–3124. [CrossRef] [PubMed]

5. Liu, R.; Rizzo, S.; Whipple, S.; Pal, N.; Pineda, A.L.; Lu, M.; Arnieri, B.; Lu, Y.; Capra, W.; Copping, R.; et al. Evaluating eligibility criteria of oncology trials using real-world data and AI. Nature 2021, 592, 629–633. [CrossRef] [PubMed]

6. Averitt, A.J.; Weng, C.; Ryan, P.; Perotte, A. Translating evidence into practice: Eligibility criteria fail to eliminate clinically significant differences between real-world and study populations. NPJ Digit. Med. 2020, 3, 67. [CrossRef] [PubMed]

7. Okuyama, A.; Higashi, T. Patterns of cancer treatment in different age groups in Japan: An analysis of hospital-based cancer registry data, 2012–2015. Jpn. J. Clin. Oncol. 2018, 48, 417–425. [CrossRef]

8. Hilgers, R.; König, F.; Molenberghs, G. Design and analysis of clinical trials for small rare disease populations. J. Rare Dis. Res. Treat. 2016, 1, 53–60. [CrossRef]

9. Latimer, N.R. Survival analysis for economic evaluations alongside clinical trials—Extrapolation with patient-level data: Inconsis- tencies, limitations, and a practical guide. Med. Decis. Mak. 2013, 33, 743–754. [CrossRef]

10. Corrigan-Curay, J.; Sacks, L.; Woodcock, J. Real-world evidence and real-world data for evaluating drug safety and effectiveness. J. Am. Med. Assoc. 2018, 320, 867–868. [CrossRef]

11. Katkade, V.B.; Sanders, K.N.; Zou, K.H. Real world data: An opportunity to supplement existing evidence for the use of long-established medicines in health care decision making. J. Multidiscip. Healthc. 2018, 11, 295–304. [CrossRef] [PubMed]

12. Gerstein, H.C.; McMurray, J.; Holman, R.R. Real-world studies no substitute for RCTs in establishing efficacy. Lancet 2019, 393, 210–211. [CrossRef]

13. Wang, S.V.; Schneeweiss, S.; Gagne, J.J.; Evers, T.; Gerlinger, C.; Desai, R.; Najafzadeh, M. Using real-world data to extrapolate evidence from randomized controlled trials. Clin. Pharmacol. Ther. 2019, 105, 1156–1163. [CrossRef] [PubMed]

14. Makady, A.; de Boer, A.; Hillege, H.; Klungel, O.; Goettsch, W. What is real-world data? A review of definitions based on literature and stakeholder interviews. Value Health 2017, 20, 858–865. [CrossRef]

15. Jansana, A.; Del Cura, I.; Prados-Torres, A.; Cuesta, T.S.; Poblador-Plou, B.; Miguel, A.G.; Lanzuela, M.; Ibañez, B.; Tamayo, I.; Moreno-Iribas, C.; et al. Use of real-world data to study health services utilisation and comorbidities in long-term breast cancer survivors (the SURBCAN study): Study protocol for a longitudinal population-based cohort study. BMJ Open 2020, 10, e040253. [CrossRef]

16. Kang, J.; Cairns, J. Protocol for data extraction: How real-world data have been used in the National Institute for Health and Care Excellence appraisals of cancer therapy. BMJ Open 2022, 12, e055985. [CrossRef]

17. Ministry of Health, Labour and Welfare. Medical Facility Survey of Japan 2020, Ministry of Health, Labour and Welfare Web Site. Available online: https://www.mhlw.go.jp/toukei/saikin/hw/iryosd/m20/dl/is2003_01.pdf (accessed on 30 April 2022). (In Japanese)

18. Hayashida, K.; Murakami, G.; Matsuda, S.; Fushimi, K. History and profile of diagnosis procedure combination (DPC): Develop- ment of a real data collection system for acute inpatient care in Japan. J. Epidemiol. 2021, 31, JE20200288. [CrossRef]

19. National Cancer Center, Japan. The Standardised Roles for Hospital Based Cancer Registries. Available online: https://ganjoho. jp/med_pro/cancer_control/can_reg/hospital/regulation.html17 (accessed on 30 April 2022). (In Japanese)

20. Okuyama, A.; Watabe, M.; Makoshi, R.; Takahashi, H.; Tsukada, Y.; Higashi, T. Impact of the COVID-19 pandemic on the diagnosis of cancer in Japan: Analysis of hospital-based cancer registries. Jpn. J. Clin. Oncol. 2022, 52, 1215–1224. [CrossRef]

21. Brierley, J.D.; Gospodarowicz, M.K.; Wittekind, C. TNM Classification of Malignant Tumours Stage, 8th ed.; Wiley-Blackwell: Hoboken, NJ, USA, 2016.

22. Quan, H.; Sundararajan, V.; Halfon, P.; Fong, A.; Burnand, B.; Luthi, J.-C.; Saunders, L.D.; Beck, C.A.; Feasby, T.E.; Ghali, W.A. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med. Care 2005, 43, 1130–1139. [CrossRef]

23. Japan Clinical Oncology Group. Common Terminology Criteria for Adverse Events v. 5.0 Japanese Translation JCOG Version (CTCAE v. 5.0-JCOG). 2017. Available online: http://www.jcog.jp/doctor/tool/CTCAEv5.0J_20180915_miekeshi_v21_1.pdf (accessed on 30 April 2022).

24. Kuk, A.Y.C.; Chen, C.-H. A mixture model combining logistic regression with proportional hazards regression. Biometrika 1992, 79, 531–541. [CrossRef]

25. Miltenberger, R.; Götte, H.; Schüler, A.; Jahn-Eimermacher, A. Progression-free survival in oncological clinical studies: Assessment time bias and methods for its correction. Pharm. Stat. 2021, 20, 864–878. [CrossRef] [PubMed]

26. Aleksakhina, S.N.; Imyanitov, E.N. Cancer therapy guided by mutation tests: Current status and perspectives. Int. J. Mol. Sci. 2021, 22, 10931. [CrossRef] [PubMed]

27. Lewandowska, A.; Rudzki, G.; Lewandowski, T.; Prochnicki, M.; Rudzki, S.; Laskowska, B.; Brudniak, J. Quality of life of cancer patients treated with chemotherapy. Int. J. Environ. Res. Public Health 2020, 17, 6938. [CrossRef] [PubMed]

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