Do we Need to Perform Bone Marrow Examination in all Subjects Suspected of MDS? Evaluation and Validation of Non-Invasive (Web-Based) Diagnostic Algorithm

Abstract

Background: Bone marrow examination (BME) is the gold standard of diagnosing myelodysplastic syndromes (MDS).

Problems: it is invasive, painful, causing possible bleeding, inaccurate (aspirate hemodilution), and subjective (inter-observer interpretation discordance). We developed non-invasive diagnostic tools: A logistic regression formula [LeukRes 2018], then a web algorithm using 10 variables (age, gender, Hb, MCV, WBC, ANC, monocytes, PLT, glucose, creatinine) to diagnose/exclude MDS [BldAdv 2021]. Here, we perform external validation of the model.

Methods: From the TASMC BM registry (2019-22) we identified and compared the model performance between MDS patients and controls (> 50 year with unexplained anemia, not MDS), all BME diagnosed, and not used in model building.

Results: The model was accurate and predicted MDS in 63% of 103 patients, and excluded (correctly) in 83% of 101 controls. It miss-classified in 11%/7% respectively, and was indeterminate in 26%/10% respectively. The positive predictive value (PPV), NPV, sensitivity, and specificity (excluding the indeterminate group) were 90%, 88%, 86%, and 92%, respectively. Subgroup (Lower/higher risk, LR/HR) analysis results were similar.

Conclusions: The MDS diagnostic model was validated and can be used, mainly for MDS exclusion, especially in suspected LR-MDS, avoiding BME in some patients. In the future incorporating peripheral blood genetics and morphometry can further improve the model.

Keywords: diagnostic model; gradient boosted model; myelodysplastic syndromes; validation.