Multicentric Assessment of a Multimorbidity-Adjusted Disability Score to Stratify Depression-Related Risks Using Temporal Disease Maps: Instrument Validation Study (Preprint)

Abstract

BACKGROUND Multimorbidity management, a growing healthcare concern, necessitates precise health risk assessment (HRA) tools to increase the efficacy of its interventions and mitigate the disease burden. However, existing solutions often fall short of accurately predicting disease progression and the emergence of new comorbid conditions, hindering the implementation of preventive measures. In contrast, research on disease trajectories has provided valuable insights into the temporal patterns of disease occurrence, enabling the identification of causal relationships between concurrent diseases. The integration of these areas of study is crucial for developing next-generation health risk assessment tools that comprehensively consider the current burden of morbidity and the risk of multimorbidity progression based on disease trajectories. OBJECTIVE Utilizing the major depressive disorder (MDD) as use case, the research aimed at generating a novel HRA tool to identify at-risk citizens. Allowing to: 1) Quantify the impact of MDD and its comorbidities on individuals and healthcare systems. And 2) Anticipate multimorbidity progression; thereby facilitating the development of preventive strategies. METHODS In the EU project TRAJECTOME, we used a novel methodology for filtering disease-disease indirect associations and identifying temporal disease maps of depression and highly prevalent co-occurring disease conditions. This information was combined with disability weights established by the Global Burden of Disease Study 2019 to create a depression-related HRA tool, the Multimorbidity Adjusted Disability Score (MADS). MADS was used to independently stratify over one million cases from three different cohorts from Spain, UK and Finland; and evaluate the correspondence among the different risk strata and the impact on the mortality rates, utilisation of healthcare resources, pharmacological burden, healthcare expenditure and multimorbidity progression. RESULTS Results indicate statistically significant associations between MADS risk strata and increased mortality rate (P <.001), heightened healthcare utilization (i.e. primary care visits P <.001; specialized care outpatient consultations P <.001; visits in mental health specialized centres P <.001; emergency room visits P <.001; hospitalizations P <.001), increased pharmacological (P <.001) and non-pharmacological expenditures (P <.001), and a raised pharmacological burden (antipsychotics P <.001; anxiolytics P <.001; hypnotics and sedatives P <.001; antidepressants P <.001). The analysis revealed an augmented risk of disease progression within the high-risk groups, as indicated by a heightened incidence of new-onset depression-related illnesses within a 12-month period after MADS assessment. CONCLUSIONS MADS seems to be a promising approach to predict depression-related health risks, and estimate multimorbidity-adjusted risk of disease progression, which can be tested in other diseases; nevertheless, clinical validation is still necessary.