Background

Bortezomib is a common multiple myeloma therapy that can cause treatment-related peripheral neuropathy, a risk factor for falls. The relationship between bortezomib and falls in older patients with multiple myeloma is unknown.

Methods

We analyzed the SEER-Medicare database for patients aged 65 or older diagnosed with multiple myeloma between 2007 and 2013. Claims were analyzed for myeloma treatments, falls, and covariates of interest. We evaluated accidental falls occurring within 12 months after starting first-line multiple myeloma treatment with bortezomib.

Results

Bortezomib was used in first-line therapy for 2052 older adults with new diagnoses of multiple myeloma. Claims for falls were reported in 157 (8%) patients within 12 months after starting bortezomib, compared to 102 (5%) patients not receiving bortezomib (p < 0.001). Bortezomib was associated with a 36% increased risk of falls after controlling for covariates (aHR 1.36; 95% CI 1.05-1.75; p = 0.018). In a landmark analysis of those who survived 12 months after starting treatment, the median overall survival of those with a fall was 35.7 months compared to 49.1 months for those without (p < 0.0001). A fall in the first year after diagnosis was associated with a 26% increased risk in hazard for death (aHR 1.26; 95% CI 1.02-1.56; p = 0.033).

Conclusion

In older adults with multiple myeloma, bortezomib was associated with an increased risk of having a diagnostic code for falls. Decreased overall survival was seen in those who fell within the year of starting therapy. Prospective trials involving fall assessments and fall-prevention interventions are needed in this population.

Background

Carfilzomib improves survival in patients with recurrent myeloma. Given the strict eligibility criteria in clinical trials, the actual frequency of cardiac adverse events (CAEs) and pulmonary adverse events (PAEs) and the risk factors associated with these AEs in the general population need to be established.

Methods

The authors extracted myeloma cases in the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database from 2000 through 2013 and corresponding claims through 2014. They then identified patients who received carfilzomib during their disease course. Subsequently, the International Classification of Diseases, Ninth Revision (ICD-9) was used to identify all the codes for CAEs, PAEs, and respiratory infections associated with carfilzomib use. Preexisting diagnoses corresponding to the CAEs and PAEs of interest were excluded to distinguish toxicity from comorbidity. Multivariate Cox regression was performed to determine those variables independently associated with the development of CAEs and PAEs.

Results

Of the 635 patients analyzed, the median age was 72 years (range, 36-94 years); 55% of the patients were male and 79% were white. The median duration of carfilzomib treatment was 58 days (range, 1-716 days). Overall, approximately 66% of the patients had codes for either CAEs or PAEs. In terms of CAEs, approximately 22% of patients developed hypertension, 15% developed peripheral edema, and 14% experienced heart failure. With regard to PAEs, approximately 28% of patients developed dyspnea, 15% developed cough, and 15% developed pneumonia. Only chronic obstructive pulmonary disease (COPD) was found to be independently associated with the development of CAEs. Patients with preexisting COPD were found to have a 40% increase in their hazard of developing CAEs (adjusted hazard ratio, 1.40; 95% CI, 1.03-1.90).

Conclusions

In older adults with myeloma who are undergoing treatment with carfilzomib, new cardiac and pulmonary diagnoses were common. Patients with preexisting COPD were found to be at an increased risk of developing CAEs.

INTRODUCTION/BACKGROUND: This study aimed to describe patient and caregiver preferences for treatments of relapsed or refractory multiple myeloma (MM). MATERIALS AND METHODS: A survey including discrete-choice experiment (DCE) and best-worst scaling (BWS) exercises was conducted among US patients with relapsed or refractory MM and their caregivers. The DCE included six attributes with varying levels including progression-free survival (PFS), toxicity, and mode and frequency of administration. In addition, the impact of treatment cost was assessed using a fixed-choice question. The BWS exercise included 18 items (modes and frequency of administration, additional treatment convenience, and toxicity items). The survey was administered online to patients recruited from the Multiple Myeloma Research Foundation CoMMpass study (NCT01454297). RESULTS: The final samples consisted of 94 patients and 32 caregivers. Avoiding severe nerve damage was most important to patients, followed by longer PFS. Caregivers considered PFS to be the most important attribute. We estimate that a third or more of patients were cost-sensitive, meaning their treatment preference was altered based on cost implications. Caregivers were not cost-sensitive. The three most bothersome treatment features in the BWS exercise were risk of kidney failure, lowering white blood cell counts, and weakening the immune system. CONCLUSION: Patients with relapsed or refractory MM and their caregivers consider many factors including efficacy, toxicity, mode/frequency of administration, and cost in their decisions regarding treatment options. The study provides a basis for future Research on patient and caregiver treatment preferences, which could be incorporated into shared decision-making with physicians.

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.