Medications Predict Lymphoma, CLL, MM Prognosis
Polypharmacy: A Surprising Predictor of Outcomes in Lymphoid Cancers
New Study Highlights Medication Burden as a Key Prognostic Indicator
A recent study published in Hemasphere suggests that the number of medications a patient takes before a lymphoid cancer diagnosis can be a powerful, self-reliant predictor of their overall survival, hospitalization rates, and risk of severe infection. Researchers examined the medication history of nearly 47,000 patients diagnosed with lymphoma, chronic lymphocytic leukemia (CLL), or multiple myeloma (MM), finding a clear correlation between a higher medication burden and poorer outcomes.
Medication Use as a Proxy for Multimorbidity
Traditionally, multimorbidity-the presence of multiple chronic conditions-has been assessed through clinical evaluations and diagnostic codes. Though, this new research, led by Brieghel and colleagues, explored the prognostic value of polypharmacy (the use of multiple medications) as a direct proxy for multimorbidity in patients with lymphoid cancers. Denmark, with its thorough prescription registry were most drugs require a prescription, provided an ideal setting for this analysis.
The study analyzed a one-year prediagnostic medication history for 46,803 newly diagnosed patients. the data was categorized by drug class,polypharmacy,and the total number of prescription medications. These metrics were then compared against key patient outcomes: overall survival (OS), hospitalization rates, and severe infection rates. Crucially, the findings were adjusted for confounding factors such as age and sex to isolate the impact of medication use.
The Dose-Response Relationship: More Medications, Worse Outcomes
The results revealed a significant association between polypharmacy and adverse outcomes.Patients taking multiple medications faced a higher risk, with a hazard ratio (HR) of 1.4 for OS, hospitalization, and severe infection (P < .001).
Furthermore, a clear dose-response relationship emerged.Patients taking 0 to 3 medications had a baseline HR of 1.0 for OS. This risk escalated with each increase in medication count:
4 to 7 medications: HR of 1.2 for OS
8 to 11 medications: HR of 1.4 for OS
More than 11 medications: HR of 1.9 for OS
This pattern was mirrored in the data for hospitalization and severe infection rates, underscoring the pervasive negative impact of a higher medication load.
Drug Classes and Their prognostic Importance
Beyond the sheer number of medications, the specific classes of drugs patients were taking also held prognostic significance. The study identified certain drug classes associated with poorer outcomes, including immunostimulants and blood substitutes, which had a significant negative impact on OS. Conversely, gynecologicals and sex hormones were linked to more favorable outcomes.
The researchers posited that patients taking immunostimulants or blood substitutes might have already initiated supportive therapies prior to their cancer diagnosis, potentially indicating a more advanced or complex disease state. In contrast, the association with favorable outcomes for gynecologicals and sex hormones was likely influenced by the demographic profile of these patients, who were more frequently enough young and female. Even after adjusting for age and sex, sex hormones retained a positive prognostic value for OS.
The authors concluded that the observed associations likely reflect patient selection-meaning that patients requiring more medications may have underlying health conditions that independently influence their outcomes-rather than a direct causal effect of the medications themselves. Though, they emphasized that their study was not designed to establish causality.
Implications for clinical Practice and Research
The study also found that for patients with Hodgkin lymphoma,mantle cell lymphoma,and MM,the time to the next treatment shortened with each additional medication prescribed.
Brieghel and colleagues assert that the number of medications a patient is taking is a robust, independent prognostic indicator. They recommend that this metric be considered a key baseline characteristic in both randomized clinical trials and routine clinical practice for patients diagnosed with lymphoid cancers. This insight could lead to more personalized treatment strategies and better risk stratification for this patient population.
References
- Brieghel C, Lacoppidan T, Packness E, et al. Polypharmacy independently predicts survival,hospitalization,and infections in patients with lymphoid cancer. hemasphere. 2025;9(7):e70172. doi:10.1002/hem3.70172
- Li Y, Zhang X, Yang L, et al. Association between polypharmacy and mortality in the older adults: A systematic review and meta-analysis. Arch Gerontol Geriatr*. 2022; 100: 104630. DOI: 10.101