Charalampous, Charalampos

PURPOSE This analysis aimed to contextualize the symptoms of peripheral neuropathy (PN) experienced by patients with triple-class refractory (TCR) multiple myeloma (MM) treated with elranatamab in the MagnetisMM-3 clinical trial with those experienced by patients with TCR MM receiving a new line of physician's choice of therapy in the real-world MagnetisMM-14 study. METHODS MagnetisMM-3 included 123 patients and MagnetisMM-14 included 35 who had TCR MM and were enrolled under the same eligibility criteria. Patient-reported symptoms of PN were collected monthly using the Chemotherapy-Induced Peripheral Neuropathy-20 item (CIPN20) questionnaire and compared for clinically meaningful differences across sensory, motor, and autonomic domains. Higher scores indicated worse patient-reported PN symptoms. RESULTS Baseline demographics and clinical characteristics for patients in MagnetisMM-3 and MagnetisMM-14 were generally similar. Patients in MagnetisMM-3 had a median of five ( v four in MagnetisMM-14) prior lines of therapy. In MagnetisMM-14, common index therapies included elotuzumab + pomalidomide (23%), carfilzomib + pomalidomide (19%), or carfilzomib + cyclophosphamide (19%), all with corticosteroids. Mean scores for sensory (15.8 v 14.8) and motor (14.4 v 12.2) domains of the CIPN20 were similar between MagnetisMM-3 and MagnetisMM-14 at baseline. Mean scores for the autonomic domain were 14.0 versus 21.3 at baseline, respectively. No clinically meaningful differences for any domain were found between month 6 scores or changes in scores from baseline to month 6 between MagnetisMM-3 and MagnetisMM-14 populations. CONCLUSION These findings suggest that elranatamab treatment was not associated with a worsening of patient-reported PN symptoms across the sensory, motor, and autonomic domains of the CIPN20. Moreover, PN symptoms reported with elranatamab treatment were similar to those reported with other common therapies used in real-world clinical practice for the management of MM. MagnetisMM-3 ClinicalTrials.gov identifier: NCT04649359 .

Introduction: In myeloma, accurate risk stratification remains a challenge due to substantial biological heterogeneity and highly variable survival outcomes. Cross-sectional imaging is commonly obtained at the time of diagnosis, but imaging findings are not currently incorporated into risk stratification efforts in a standardized manner, despite their prognostic significance. Here, we investigate the use of novel image-based prognostic biomarkers obtained by automated image segmentation and radiomics feature extraction using machine learning methods. Methods: We obtained the pre-treatment 18F-FDG PET/CT scans of 443 patients with newly diagnosed myeloma and complete demographic and cytogenetic data (seen at Mayo Clinic between 2005 and 2019). The native DICOM images were pre-processed and subjected to automated image segmentation using nnU-Net (v1.0, inference using a pre-trained hematologic malignancies model). Limitations of this automated segmentation approach include heterogeneity introduced by varying image quality, technical differences related to PET reconstruction, and potential inclusion of non-neoplastic FDG-avid lesions in segmented regions. The quality of the automated image segmentation was evaluated by comparing the radiomics features obtained from ground-truth segmentation (manual lesion segmentation) and model segmentation in a separate cohort of patients with hematologic malignancies (n=72). We selected 42 radiomics features that moderately (r≥0.30, p<0.005, n=23) or strongly (r≥0.50, p<0.001, n=19) correlated between ground-truth (manual) and model (automated) segmentation for further evaluation in myeloma patients. PyRadiomics was used to extract discrete radiomics features for clinical prediction modeling. We evaluated the prognostic significance of tumor size-, shape-, and texture-related radiomics features and compared their predictive power to established prognostic factors (International Staging System [ISS], Revised ISS [R-ISS] stage and high-risk FISH cytogenetics). The outcome of interest was overall survival and the predictive power of competing proportional hazards regression models was assessed using Harrell's C-statistic. For modeling purposes, patients without measurable tumor volume were categorized as having undetectable radiomics features (0 for all features). All radiomics features were median dichotomized for downstream modeling. Forward feature selection and testing for multicollinearity were used to remove redundant features. Select radiomics features were divided into quintiles to generate an additive radiomics risk score and associated risk strata. Results: Median age at diagnosis of the 443 myeloma patients was 63 years (32-91) and 270 patients (62%) were men. After a median follow-up of 2.4 years (95% CI 0.1-7.4), median overall survival was 6.5 years (95% CI 5.5-NR). Most patients had detectable metabolic tumor volume (n=309, 70%) on their pre-treatment 18F-FDG PET/CT scan. Several of the 42 radiomics features were intercorrelated and two features were selected for further investigation based on their independent prognostic significance (forward feature selection). Higher maximum axial tumor diameter (HR 1.90, 95% CI 1.31-2.76, p=0.001) and a lower concentration of low gray-level values in the tumor (HR 1.73, 95% CI 1.20-2.49, p=0.004) were independently associated with overall survival in newly diagnosed myeloma. These associations were independent of age at diagnosis, sex, and R-ISS stage. We devised a simple additive risk score representing the sum of quintiles of the two radiomics features and divided the patients into three risk categories akin to the R-ISS. The predictive power of this radiomics risk score (Harrell's C=0.60) was comparable to the ISS (C=0.59) and the R-ISS (C=0.57). Conclusions: Automated image segmentation and radiomics feature extraction from 18F-FDG PET/CT scans is feasible. This approach yields image-based biomarkers that correlate with results obtained by manual imaging segmentation. Several radiomics features such as tumor size and heterogeneity have independent prognostic significance in newly diagnosed myeloma. These novel biomarkers rival the predictive power of the currently established risk stratification methods and may be used to improve risk stratification in myeloma.

Abstract As patients with relapsed/refractory multiple myeloma (RRMM) continue to live longer, they might get exposed to most available drugs and drug classes during the disease course. For such late line RRMM or among patients without access to novel therapies, retreatment with a drug that the disease had previously been refractory to might be one option. In this retrospective study, we describe 315 patients with RRMM at our institution who were retreated with a drug that the disease had been previously refractory to. We found an overall response rate of 56.2% and a median progression-free survival (PFS) of 11 months with retreatment. Patients with a longer time on initial therapy with the index drug (>28.4 months) had a superior PFS with retreatment (median PFS, 16.9 vs 8.1 months; P < .001). Similarly, patients with a longer time gap between the initial line of therapy with index drug and retreatment with index drug (>46.1 months) had better PFS with retreatment (28.2 vs 8.9 months; P = .016). In conclusion, retreatment with a previously refractory drug is a viable therapeutic option for RRMM, with the most significant benefit derived in disease demonstrating sensitivity to initial drug exposure and among those with a longer gap between initial drug exposure and retreatment.

Abstract Lenalidomide‐containing (R) triplet and quadruplet regimens are the standard of care for multiple myeloma (MM) and have been shown to increase the risk of thrombosis. The association between thromboembolism (TE) and survival in the novel multidrug era is not yet delineated. In this study, we evaluated the incidence of TE during the first year of MM diagnosis, its association with the type of induction regimen, and its impact on overall survival. We studied 672 newly diagnosed MM (NDMM) patients who received a triplet or quadruplet lenalidomide‐based induction at the Mayo Clinic, Rochester. TE was diagnosed in 83 patients (12.4%). Of these, 56 (8.3%) had a deep venous thrombosis (DVT), 23 (3.4%) had a pulmonary embolism (PE) with or without the DVT, and 4 (0.6%) patients had a stroke. Carfilzomib‐Rd (KRd) had the highest risk of TE (21.1%, 18/85), followed by quadruplets (11.1%, 5/45), bortezomib‐Rd (9.6%, 51/531), and 0/11 (0%), treated with other lenalidomide‐containing regimens. The difference in TE risk between KRd and the other regimens was statistically significant (OR = 2.6, p < .01). Nine patients developed a TE before being exposed to any treatment. Survival was significantly lower among patients that developed a TE (66 vs. 133 months, p < .01). The association of TE with reduced survival demonstrated in univariate analysis (HR = 2.2, 95% CI = 1.6–3.3) was maintained in the multivariable analysis adjusted for high‐risk interphase fluorescence in situ hybridization (FISH), sex, age, receipt of an upfront transplant, the response at induction, and the International Staging System (ISS) (HR = 2.61, CI = 1.74–3.9). We conclude that TE is an important aspect of MM management, and effective management is especially relevant in the novel treatment era.