Assessment of Predictive Factors That Shorten Duration of Treatment in Patients With Multiple Myeloma Using AI: Real-World Longitudinal Study Using Data From Medical Data Vision Claims Database

Hiroshi Handa   ¹ , MD, PhD ;   Tadao Ishida   ² , MD, PhD ;   Shuji Ozaki   ³ , MD, PhD ;   Shinsuke Iida   ⁴ , MD, PhD ;   Kittima Wattanakamolkul   ⁵ , BSc, MSc, PhD ;   Chika Sakai   ⁶ , BPharm ;   Kenichi Kato   ⁶ , BSIS ;   David Bin-Chia Wu   ^{7, 8, 9} , MSc, PhD, BSc ;   DaeYoung Yu   ⁷ , BSc, MPH, PhD ;   Shota Nemoto   ¹⁰ , MIB, BE ;   Yasuho Yamashita   ¹¹ , PhD ;   Takuma Shibahara   ¹¹ , PhD

¹ Department of Hematology, Gunma University Hospital, Gunma, Japan

² Department of Hematology, Japanese Red Cross Medical Center, Tokyo, Japan

³ Department of Hematology, Tokushima Prefectural Central Hospital, Tokushima, Japan

⁴ Department of Hematology and Oncology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan

⁵ Value, Evidence and Access Department, Integrated Market Access, Johnson & Johnson, Tokyo, Japan

⁶ Medical Affairs, Johnson & Johnson, Tokyo, Japan

⁷ Asia Pacific Regional Market Access, Johnson & Johnson, Singapore, Singapore

⁸ Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore

⁹ School of Pharmacy, Faculty of Health & Medical Sciences, Taylor’s University Malaysia, Malaysia, Malaysia

¹⁰ Industrial & Digital Business Unit, Hitachi (Japan), Tokyo, Japan

¹¹ Research and Development Group, Hitachi (Japan), Tokyo, Japan