Mechanism: Combining endemic exposure history with eosinophil count creates a more accurate screening rule for Strongyloides infection in autoimmune patients. Readout: Readout: This combined model outperforms eosinophilia alone, showing higher AUROC and net benefit for predicting positive serology or treatment decisions.
Claim In adults with rheumatic or autoimmune disease who are about to start prolonged glucocorticoids, a screening rule that combines endemic-exposure history with baseline eosinophil count will identify treatment-relevant Strongyloides stercoralis infection more accurately than eosinophilia alone.
Rationale Eosinophilia is useful but incomplete: some infected patients have normal eosinophil counts, while some eosinophilic autoimmune patients are parasite-negative. Exposure history captures prior biologic plausibility that laboratory data alone can miss. In practice, both variables are available before steroids and therefore can be tested as a pragmatic bedside rule.
Testable prediction
A two-variable model (endemic exposure + eosinophilia) will show higher AUROC and net benefit than eosinophilia alone for predicting either positive Strongyloides serology or a clinician decision to treat before high-dose immunosuppression.
Suggested study design
- Prospective multicenter cohort of autoimmune patients screened before ≥20 mg/day prednisone-equivalent for ≥2 weeks, pulse steroids, rituximab, or cyclophosphamide
- Predefine endemic exposure categories and eosinophil thresholds
- Primary endpoint: positive serology and/or treatment-triggering parasitologic result
- Secondary endpoint: hyperinfection, disseminated disease, or gram-negative sepsis within 90 days after immunosuppression
- Analysis: compare AUROC, calibration slope, decision-curve analysis, and sensitivity at clinically relevant thresholds
Falsification condition If the combined model does not outperform eosinophilia alone in discrimination or clinical net benefit, the hypothesis fails.
Limitations Exposure history may be misclassified, and serology performance varies by immune state and assay.
References
- Fragoulis GE, et al. Ann Rheum Dis. 2023;82(6):742-753. DOI: 10.1136/ard-2022-223335
- Requena-Mendez A, et al. Am J Trop Med Hyg. 2017;97(3):645-652. DOI: 10.4269/ajtmh.16-0923
- Ming DK, et al. Trop Med Infect Dis. 2021;6(4):203. DOI: 10.3390/tropicalmed6040203
- Buonfrate D, et al. Pathogens. 2020;9(6):468. DOI: 10.3390/pathogens9060468
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