Predictors of DM1 Patient Survival

Published on Fri, 03/09/2018

Analysis of phenotypic variability in the presentation of DM1 has led to the conclusion that disease types based upon age of onset represent a continuum, but that there are recognizable patterns in symptom onset and progression (De Antonio et al., 2016) that impact prognosis. Gender is also a major modifier of symptomatology and, ultimately, of mortality rates (Dogan et al., 2016). Understanding these risk factors and how they contribute toward the clinical spectrum and stages of DM1 is critically important for appropriate management of patient care and for the design of clinical trials.

Implementation of the care considerations developed by the MDF in partnership with an international group of physicians represents a critically important step in improving the quality of life for those living with myotonic dystrophy. Development of a means to quantitatively assess the risk factors of and long-term prognosis for this multi-systemic disease at the individual patient level would provide an important tool for patient management.

Towards a Prognostic System for DM1 Patient Survival

To determine whether a clinical scoring model might predict long-term survival, Dr. Karim Wahbi (Cochin Hospital, Sorbonne Paris Cité University) and colleagues assessed a cohort of 1296 consecutive adult patients with molecular confirmation of DM1 and included in the French DM1 Heart Registry (Wahbi et al., 2018). 1066 patients were used in a derivation cohort to identify and assign weighting of variables that would comprise a survival index, while the remainder of patients, all from two other clinics, served as a validation cohort. The primary study endpoint was survival and ten variables collected in the DM1 Heart Registry were evaluated for inclusion in a prognostic index.

The commonly available variables of age, diabetes, need for support when walking, heart rate, systolic blood pressure, first-degree atrioventricular block, bundle-branch block, and lung vital capacity were associated with death. These factors were associated with survival by multiple variable Cox modeling and found to contribute to a prognostic model. CTG length, atrial fibrillation, left ventricular dysfunction, and dysphagia did not add to the predictive value of the scoring system and were excluded. Scores ranging from 1 or less to 15 or more were associated with 10-year survival probabilities from 98.1% to 22.5%, respectively. Thus, the model exhibited a wide dynamic range in predicting survival. Survivors and non-survivors were similarly well discriminated in the validation cohort.

A Simplified Tool for Patient Management and Clinical Trial Design

The research team emphasized the value of the DM1 survival score by noting that just eight common patient traits typically collected in clinical examinations are needed to determine a score. Moreover, the reliability and long-term prognostic capability may make this system an essential tool in the management of care in a multi-disciplinary setting.

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