Efficacy of Risankizumab across distinct PsA phenotypes identified with machine learning analytics using data from biologic DMARD-Naïve patients in two phase 3 clinical trials
Laure Gossec, Andra Balanescu, Maria Antonietta D’Agostino, Alexis Ogdie, Philipp Sewerin, Yu Deng, Linyu Shi, Yoshiyuki Sugimoto, Sheng Zhong, Yunzhao Xing, Ralph Lippe, Mitsumasa Kishimoto · 2025
Read Efficacy of Risankizumab across distinct PsA phenotypes identified with machine learning analytics using data from biologic DMARD-Naïve patients in two phase 3 clinical trials by Laure Gossec, Andra Balanescu, Maria Antonietta D’Agostino, Alexis Ogdie, Philipp Sewerin, Yu Deng, Linyu Shi, Yoshiyuki Sugimoto, Sheng Zhong, Yunzhao Xing, Ralph Lippe, Mitsumasa Kishimoto (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12771703.txt.
Description
Laure Gossec and colleagues sorted psoriatic arthritis patients by computer in 2025. Personal care is hard without clear patient types. Machine learning can find uniform groups in trial data. The team reanalyzed two large phase three trials. Patients were new to biologic drugs at entry. All received the same immune drug for up to four years. An unsupervised model grouped patients by starting traits. Response meant minimal or low disease activity at four years.
Five distinct patient types emerged from the model. The largest group carried moderate to high activity. Other groups centered on large joints, hands, or feet. Swollen finger and toe patterns marked two groups. The drug worked across all five types. Response ranges stayed solid in every group. The largest group and the feet group responded best. The authors call typing a first step toward personal care.
Catalog record
| CREATOR | Laure Gossec, Andra Balanescu, Maria Antonietta D’Agostino, Alexis Ogdie, Philipp Sewerin, Yu Deng, Linyu Shi, Yoshiyuki Sugimoto, Sheng Zhong, Yunzhao Xing, Ralph Lippe, Mitsumasa Kishimoto |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 38 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |