SwePub
Tyck till om SwePub Sök här!
Sök i LIBRIS databas

  Utökad sökning

hsv:(MEDICIN OCH HÄLSOVETENSKAP) hsv:(Klinisk medicin) hsv:(Reumatologi och inflammation)
 

Sökning: hsv:(MEDICIN OCH HÄLSOVETENSKAP) hsv:(Klinisk medicin) hsv:(Reumatologi och inflammation) > (2020-2021) > Predicting response...

Predicting response to tocilizumab monotherapy in rheumatoid arthritis: A real-world data analysis using machine learning

Johansson, Fredrik, 1988 (författare)
Chalmers tekniska högskola,Chalmers University of Technology
Collins, Jamie (författare)
Brigham and Women's Hospital
Yau, Vincent (författare)
Genentech Inc.
visa fler...
Guan, Hongshu (författare)
Brigham and Women's Hospital
Kim, Seoyoung C. (författare)
Brigham and Women's Hospital
Losina, Elena (författare)
Brigham and Women's Hospital
Sontag, D. (författare)
Massachusetts Institute of Technology (MIT)
Stratton, Jacklyn (författare)
Brigham and Women's Hospital
Trinh, Huong (författare)
Genentech Inc.
Greenberg, Jeffrey (författare)
New York University
Solomon, Daniel H. (författare)
Brigham and Women's Hospital
visa färre...
 (creator_code:org_t)
2021-05-01
2021
Engelska.
Ingår i: Journal of Rheumatology. - : The Journal of Rheumatology. - 1499-2752 .- 0315-162X. ; 48:9, s. 1364-1370
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Objective. Tocilizumab (TCZ) has shown similar efficacy when used as monotherapy as in combination with other treatments for rheumatoid arthritis (RA) in randomized controlled trials (RCTs). We derived a remission prediction score for TCZ monotherapy (TCZm) using RCT data and performed an external validation of the prediction score using real-world data (RWD). Methods. We identified patients in the Corrona RA registry who used TCZm (n = 452), and matched the design and patients from 4 RCTs used in previous work (n = 853). Patients were followed to determine remission status at 24 weeks. We compared the performance of remission prediction models in RWD, first based on variables determined in our prior work in RCTs, and then using an extended variable set, comparing logistic regression and random forest models. We included patients on other biologic disease-modifying antirheumatic drug monotherapies (bDMARDm) to improve prediction. Results. The fraction of patients observed reaching remission on TCZm by their follow-up visit was 12% (n = 53) in RWD vs 15% (n = 127) in RCTs. Discrimination was good in RWD for the risk score developed in RCTs, with area under the receiver-operating characteristic curve (AUROC) of 0.69 (95% CI 0.62-0.75). Fitting the same logistic regression model to all bDMARDm patients in the RWD improved the AUROC on held-out TCZm patients to 0.72 (95% CI 0.63-0.81). Extending the variable set and adding regularization further increased it to 0.76 (95% CI 0.67-0.84). Conclusion. The remission prediction scores, derived in RCTs, discriminated patients in RWD about as well as in RCTs. Discrimination was further improved by retraining models on RWD.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kirurgi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Surgery (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Reumatologi och inflammation (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Rheumatology and Autoimmunity (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kardiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)

Nyckelord

Disease-modifying antirheumatic drug
Machine learning
Prediction model
Rheumatoid arthritis
Remission

Publikations- och innehållstyp

art (ämneskategori)
ref (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy