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Phenotype Submission - Waldenstrom macroglobulinemia

Cohort Definition Name : Earliest event of Waldenstrom macroglobulinemia

Contributor name : ‘Jill Hardin’

Contributor OrcId :

Logic Description : Earliest occurrence of Waldenstrom macroglobulinemia indexed on diagnosis date, for the first time in history cohort exit is the end of continuous observation

Recommended study application : target

Assertion statement : This cohort definition was executed on at least one real person-level observational health data source and resulted in a cohort with at least 1 person.

Target Clinical Description : Waldenström macroglobulinemia (WM), a subtype of lymphoplasmacytic lymphoma, is a rare, slow-growing B-cell non-Hodgkin lymphoma. The disease is primarily found in the bone marrow, where abnormal B lymphocytes grow and crowd out normal blood cells. Accumulated B lymphocytes produce excessive quantities of an antibody protein known as immunoglobin M (IgM), which causes the blood to become thick (hyperviscosity) and affects the blood flow through the smaller blood vessels. WM mostly develops in people over 65, affects more men than women, and is more common in white people.

"Evaluation conclusion : We developed a prevalent cohort definition for Waldenstrom macroglobulinemia (WM) using a concept set containing concepts which incorporated all those found from the literature review and from the analysis of PHOEBE and orphan concepts in cohort diagnostics.
We performed the evaluation across a network of claim data sources and 1 EHR US data source. The data sources are: IBM® MarketScan® Commercial Database (CCAE), Optum’s longitudinal EHR repository (Optum EHR), Optum’s Clinformatics® Data Mart (DOD), IBM® MarketScan® Multi-State Medicaid Database (MDCD), IBM® MarketScan® Medicare Supplemental Database (MDCR), Japan Claims Database (JMDC), Clinical Practice Research Datalink (CPRD) , IQVIA® Australia Longitudinal Patient Data (LPD) database (Australia), IQVIA® Disease Analyzer (DA) France database (France), QVIA® Disease Analyzer (DA) Germany database (Germany), IQVIA® Adjudicated Health Plan Claims Data (formerly PharMetrics Plus) - US database (PharMetrics), IQVIA® Ambulatory EMR (EMR). The algorithm retrieves subjects from all 11 databases tested. We found that there were signs and symptoms in the period prior to the first diagnosis of WM indicative of index date misclassification. For example, codes indicating common symptoms of WM including anemia ( 439777), monoclonal gammopathy (4002359), malignant lymphoma (432571) and are found in subjects in the 30 days prior to index across all databases evaluated. However in the context of this disease the latency period is lengthy as many subjects are not officially diagnosed for years and because prevalent cohorts are being developed we opted to not use a cohort adjusted for index date misclassification. In addition, we developed 2 more specific cohorts the first requiring a second diagnosis code for WM in the time period 31-365 days after index and the second requiring a specialist visit and diagnostic code for WM. These cohort definitions improve the specificity of the algorithm albeit at the expense of sensitivity as determined by PheValuator. Because use of second codes is not common in some databases, use of codes in future can result in immortal time bias, and the use of an algorithm using 2 codes in this case does not dramatically alter the sensitivity and ppv metrics we recommend using the algorithm requiring only 1 code.
Phevaluator results show that the sensitivity varies and is lowest in the algorithm using 2 codes or a specialist visit (ranging from 0.711-0.92) and highest in the algorithm using just one code of WM (ranging from 0.77-0.98). Adding the requirement of a second diagnosis code increased the positive predictive value (PPV) for the algorithm (ranging from 0.79 to 0.97 to ranging from 0.45to 0.70) but at the expense of a decrease in sensitivity. Phevaluator results for MDCD and ex US databases (JMDC, IMS Germany, France, AUS, and CPRD) resulted in too few outcomes to produce models; hence only US results are available. Although these phenotypes exist none of them offer outstanding performance PPV in all data sources, so the user is cautioned to explicitly share the Phevaluator performance metrics when using this phenotype definition.

Imported to the OHDSI Phenotype Library. It may be expected to be found with id = 1012 in the next release. Thank you