Development and validation of a prognostic model for leflunomide discontinuation with abnormal blood-tests during long-term treatment: cohort study using data from Clinical Practice Research Datalink Gold and Aurum

Clinical prediction models for medication adverse events in patients with rheumatic and musculoskeletal conditions: A systematic literature review

OBJECTIVES

This systematic review aims to identify, summarize, and evaluate the methodological quality of existing clinical prediction models (CPMs) that predict adverse events (AEs) associated with medications prescribed for rheumatic and musculoskeletal diseases (RMDs).

METHODS

We searched PubMed, Embase, and Medline databases up to March 2024. Studies were included if they developed multivariable CPM predicting AEs in adult patients using RMD medications. Data extraction and quality assessment were conducted using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias Assessment Tool (PROBAST) checklists to ensure consistent reporting and assess the risk of bias (ROB).

RESULTS

Of 2406 studies identified, 1734 titles/abstracts were screened, and 38 were reviewed in full. Twelve studies reporting 17 CPMs met eligibility criteria. Most CPMs (76.4 %) focused on rheumatoid arthritis and disease modifying anti-rheumatic drugs (DMARDs) such as methotrexate (69.2 %) and biologic drugs (15.3 %). Cox proportional hazards or logistic regression models were commonly used. Twelve models (70.5 %) had high overall ROB due to inappropriate variable selection methods and sample size.

CONCLUSIONS

This is the first systematic review summarising CPMs for AEs associated with RMD medications. It highlights that existing CPMs are affected by methodological pitfalls, including inappropriate variable selection and lack of clear sample size justification. Future models could consider a broader range of RMDs and medications. Emerging methods such as machine learning with the ability to model complex interactions, and multi-outcome CPMs to predict several AEs to one class of drug may improve predictions.

Patient and health professional views on risk-stratified monitoring of immune-suppressing treatment in adults with inflammatory diseases

OBJECTIVE

To explore the acceptability of an individualized risk-stratified approach to monitoring for target-organ toxicity in adult patients with immune-mediated inflammatory diseases established on immune-suppressing treatment(s).

METHODS

Adults (≥18 years) taking immune-suppressing treatment(s) for at least six months, and healthcare professionals (HCPs) with experience of either prescribing and/or monitoring immune-suppressing drugs were invited to participate in a single, remote, one-to-one, semi-structured interview. Interviews were conducted by a trained qualitative researcher and explored their views and experiences of current monitoring and acceptability of a proposed risk-stratified monitoring plan. Interviews were transcribed verbatim and inductively analysed using thematic analysis in NVivo.

RESULTS

Eighteen patients and 13 HCPs were interviewed. While participants found monitoring of immune-suppressing drugs with frequent blood-tests reassuring, the current frequency of these was considered burdensome by patients and HCPs alike, and to be a superfluous use of healthcare resources. Given abnormalities rarely arose during long-term treatment, most felt that monitoring blood-tests were not needed as often. Patients and HCPs found it acceptable to increase the interval between monitoring blood-tests from three-monthly to six-monthly or annually depending on the patients' risk profiles. Conditions of accepting such a change included: allowing for clinician and patient autonomy in determining individuals' frequency of monitoring blood-tests, the flexibility to change monitoring frequency if someone's risk profile changed, and endorsement from specialist societies and healthcare providers such as the National Health Service.

CONCLUSION

A risk-stratified approach to monitoring was acceptable to patients and health care professionals. Guideline groups should consider these findings when recommending blood-test monitoring intervals.

The prescription and monitoring of conventional synthetic disease-modifying anti-rheumatic drugs: British Society for Rheumatology guideline scope

This guideline will provide up-to-date, evidence-based recommendations on the safe use of non-biologic DMARDs, also called conventional synthetic DMARDs (csDMARD), across the full spectrum of autoimmune rheumatic diseases. The guideline will update the guideline published in 2017 and will be expanded to include people of all ages. Updated information on the monitoring of DMARDs and vaccinations will be included. The guideline will be developed using the methods and processes described in the British Society for Rheumatology's 'Creating clinical guidelines: our protocol', updated 2023.

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

BACKGROUND

Sulfasalazine-induced cytopenia, nephrotoxicity and hepatotoxicity is uncommon during long-term treatment. Some guidelines recommend 3 monthly monitoring blood tests indefinitely during long-term treatment while others recommend stopping monitoring after 1 year. To rationalise monitoring, we developed and validated a prognostic model for clinically significant blood, liver or kidney toxicity during established sulfasalazine treatment.

DESIGN

Retrospective cohort study.

SETTING

UK primary care. Data from Clinical Practice Research Datalink Gold and Aurum formed independent development and validation cohorts.

PARTICIPANTS

Age ≥18 years, new diagnosis of an inflammatory condition and sulfasalazine prescription.

STUDY PERIOD

1 January 2007 to 31 December 2019.

OUTCOME

Sulfasalazine discontinuation with abnormal monitoring blood-test result.

ANALYSIS

Patients were followed up from 6 months after first primary care prescription to the earliest of outcome, drug discontinuation, death, 5 years or 31 December 2019. Penalised Cox regression was performed to develop the risk equation. Multiple imputation handled missing predictor data. Model performance was assessed in terms of calibration and discrimination.

RESULTS

8936 participants were included in the development cohort (473 events, 23 299 person-years) and 5203 participants were included in the validation cohort (280 events, 12 867 person-years). Nine candidate predictors were included. The optimism adjusted R2 D and Royston D statistic in the development data were 0.13 and 0.79, respectively. The calibration slope (95% CI) and Royston D statistic (95% CI) in validation cohort was 1.19 (0.96 to 1.43) and 0.87 (0.67 to 1.07), respectively.

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.

Prognostic factors for liver, blood and kidney adverse events from glucocorticoid sparing immune-suppressing drugs in immune-mediated inflammatory diseases: a prognostic systematic review

BACKGROUND

Immune-suppressing drugs can cause liver, kidney or blood toxicity. Prognostic factors for these adverse-events are poorly understood.

PURPOSE

To ascertain prognostic factors associated with liver, blood or kidney adverse-events in people receiving immune-suppressing drugs.

DATA SOURCES

MEDLINE, Web of Science, EMBASE and the Cochrane library (01 January 1995 to 05 January 2023), and supplementary sources.

DATA EXTRACTION AND SYNTHESIS

Data were extracted by one reviewer using a modified CHARMS-PF checklist and validated by another. Two independent reviewers assessed risk of bias using Quality in Prognostic factor Studies tool and assessed the quality of evidence using a Grading of Recommendations Assessment, Development and Evaluation-informed framework.

RESULTS

Fifty-six studies from 58 papers were included. High-quality evidence of the following associations was identified: elevated liver enzymes (6 studies) and folate non-supplementation (3 studies) are prognostic factors for hepatotoxicity in those treated with methotrexate; that mercaptopurine (vs azathioprine) (3 studies) was a prognostic factor for hepatotoxicity in those treated with thiopurines; that mercaptopurine (vs azathioprine) (3 studies) and poor-metaboliser status (4 studies) were prognostic factors for cytopenia in those treated with thiopurines; and that baseline elevated liver enzymes (3 studies) are a prognostic factor for hepatotoxicity in those treated with anti-tumour necrosis factors. Moderate and low quality evidence for several other demographic, lifestyle, comorbidities, baseline bloods/serologic or treatment-related prognostic factors were also identified.

LIMITATIONS

Studies published before 1995, those with less than 200 participants and not published in English were excluded. Heterogeneity between studies included different cut-offs for prognostic factors, use of different outcome definitions and different adjustment factors.

CONCLUSIONS

Prognostic factors for target-organ damage were identified which may be further investigated for their potential role in targeted (risk-stratified) monitoring.

PROSPERO REGISTRATION NUMBER

CRD42020208049.