Defined as a platelet count <100x109/L with no known cause, immune thrombocytopenia (ITP) is a diagnosis of exclusion, meaning other thrombocytopenic conditions must be ruled out before establishing the ITP diagnosis. This can lead to errors, unnecessary exposures to expensive and harmful treatments, and increased patient anxiety and distress. In the absence of a standardized diagnostic test, a clinical prediction model, called the Predict-ITP tool, was developed to aid hematologists in establishing the ITP diagnosis among patients who present with thrombocytopenia. Based on a cohort of 839 patients referred to an academic hematology clinic and using penalized logistic regression, the following predictor variables for the ITP diagnosis were identified: 1) high platelet variability index; 2) lowest platelet count; 3) highest mean platelet volume; and 4) history of a major bleed. Internal validation was completed using bootstrap resampling, and showed good discrimination and excellent calibration.
Following internal validation and prior to implementation, the Predict-ITP Tool must undergo external validation by evaluating the tool’s performance in a different cohort. A study protocol was developed with the objective of externally validating the Predict-ITP Tool by collecting data from 960 patients from 11 clinics across Canada. The tool will compute the probability of ITP using information available at the time of the initial consultation, and results will be compared with either the local hematologist’s diagnosis at the end of follow-up or the adjudicated diagnosis. Discrimination (the ability to differentiate between patients with and without ITP) and calibration (the agreement between predicted and actual classifications) of the tool will be assessed.
The Predict-ITP Tool must demonstrate good discrimination (c-statistic ≥ 0.8) and excellent calibration (calibration-in-the-large close to 0; calibration slope close to 1) to achieve external validation. If implemented, this tool will improve diagnostic accuracy and reduce delays in diagnosis and unnecessary treatments and investigations. / Thesis / Master of Science (MSc) / There lack of a standardized test to diagnose immune thrombocytopenia (ITP) leads to delays in care, use of incorrect treatments, and increased patient anxiety. The Predict-ITP Tool was developed to classify patients as ITP or non-ITP using the following data: 1) platelet counts in the recent past; 2) the highest mean platelet volume; and 3) major bleeding at any time in the past. The preliminary internal validation study showed promise.
I developed a study protocol to externally validate the Predict-ITP Tool that will collect data from 960 patients from 11 clinics across Canada to see how accurately the tool would have performed to classify patients as ITP or non-ITP at the first hematology visit compared with the gold standard clinical diagnosis by the hematologist or an independent expert committee. A successful external validation that demonstrates the tool’s predictive accuracy in an external population must be completed before widespread use.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29316 |
| Date | January 2023 |
| Creators | Mahamad, Syed |
| Contributors | Arnold, Donald, Medical Sciences |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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