Risk-stratified monitoring for sulfasalazine toxicity: prognostic model development and validation

RMD OpenPublished Retrospective cohort study

Authors' conclusion

This prognostic model for sulfasalazine toxicity uses readily available data and should be used to risk-stratify blood-test monitoring during established sulfasalazine treatment.

Study context

Population
UK primary care adults (≥18 years) with a new diagnosis of an inflammatory condition and a sulfasalazine prescription, 1 January 2007 to 31 December 2019Nine candidate predictors
Participants
8,936 vs 5,203
Exposure
Development vs Validation
  • Developmentn = 8,936
  • Validationn = 5,203
Outcome
Sulfasalazine discontinuation with abnormal monitoring blood-test result
Follow-up
Followed up from 6 months after first prescription to up to 5 years
Methodological detailsprognostic model development and validation, independent development and validation cohorts, penalised Cox regression, multiple imputation
  • Prognostic model development and validation
  • Independent development and validation cohorts
  • Penalised Cox regression
  • Multiple imputation

Main finding

As reported in the abstract

Model performance
GroupValuePerson-yearsOptimism adjusted R2 DRoyston D statisticCalibration slope (95% CI)Royston D statistic (95% CI)
Development473 events23 2990.130.79
Validation280 events12 8671.19 (0.96 to 1.43)0.87 (0.67 to 1.07)

Value

Development473 events
Validation280 events

Person-years

Development23 299
Validation12 867

Optimism adjusted R2 D

Development0.13
Validation— not stated in the abstract

Royston D statistic

Development0.79
Validation— not stated in the abstract

Calibration slope (95% CI)

Development— not stated in the abstract
Validation1.19 (0.96 to 1.43)

Royston D statistic (95% CI)

Development— not stated in the abstract
Validation0.87 (0.67 to 1.07)

Observational data: associations, not effects.

Original publication

Risk-stratified monitoring for sulfasalazine toxicity: prognostic model development and validation. RMD Open. Published 7 March 2024. doi:10.1136/rmdopen-2023-003980

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