A Prognostic Symptom Model Incorporating Patient-Reported Symptoms for Transplant-Ineligible Patients with Multiple Myeloma

TL;DR

A new model predicts which transplant-ineligible multiple myeloma patients will experience persistent symptoms like pain and depression, helping identify those who need early intervention.

Contribution

A novel prognostic model using patient-reported symptoms to predict future symptom burden in transplant-ineligible multiple myeloma patients.

Findings

Baseline severe pain strongly predicts future moderate-to-severe pain in patients.

Baseline tiredness and depression are the strongest predictors of future tiredness and depression.

Baseline impaired well-being is a significant predictor of future impaired well-being.

Abstract

Patients with transplant-ineligible multiple myeloma have high rates of symptom burden. We developed a tool to predict symptoms in this patient population using large datasets. Using symptoms reported by patients, we could predict who will experience persisting symptoms of pain, tiredness, depression, and impaired well-being. This tool can help identify patients who are high-risk and may benefit from psychosocial or symptom control interventions.

Introduction: Patients with transplant-ineligible (TIE) multiple myeloma (MM) have high rates of symptom burden. The aim of this study was to develop and validate a prognostic model to predict symptoms in patients with TIE MM. Methods: In this population-based, retrospective cohort study, using multiple administrative health care databases linked using a unique encrypted patient identifier in Ontario, Canada, symptoms were identified using the patient self-reported Edmonton Symptom Assessment System (ESAS) at each clinic visit. The primary outcome was the presence of moderate-to-severe (ESAS score 4–10) symptoms (specifically symptoms of pain, tiredness, depression, and impaired well-being) within one year from the index date. Using the entire cohort, a multivariable logistic regression model with baseline covariates was developed to predict the risk of experiencing each of the above symptoms, categorized as moderate to severe within 1 year post-index date. Internal validation of the model was assessed via bootstrap validation methods. Results: A total of 1535 TIE adults with MM met the inclusion criteria. The median age was 75, with 25.2% of patients aged 80 years or older. In the multivariate analysis, baseline symptoms continued to be most associated with future symptom burden. Baseline severe pain (OR 9.84, 95% CI 6.29–15.7) was most associated with patients experiencing moderate–severe pain one year post-index date. Similarly, baseline severe tiredness (OR 17.34, 95% CI 9.00–33.42), baseline severe depression (OR 28.07, 95% CI 15.96–49.38), and baseline severely impaired well-being (OR 4.12, 95% CI 2.30–7.37) were the biggest predictors of patients experiencing moderate–severe tiredness, depression, and impaired well-being, respectively, at one year after the index date. Conclusions: Patients with MM experience persisting symptoms of pain, tiredness, depression, and impaired well-being, with baseline symptoms being the biggest predictor of future symptom burden.

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