Stratifying ‘frail’ Patients Defined By the Simplified Frailty Scale in Multiple Myeloma: Correlation with Clinical Outcomes

Introduction:

Frailty assessment is crucial for predicting the prognosis and ensuring appropriate care for older patients with multiple myeloma (MM). The Simplified Frailty Scale (SFS) comprises performance status (PS) (0-2 points), age (0-2 points), and Charlson Comorbidity Index (CCI) (0 or 1 point). Scores of 0-1 define non-frail patients, whereas scores of 2-5 define frail patients; frail patients have a significantly worse prognosis (Facon T et al. Leukemia 2020). However, because the frail group includes those with SFS scores of 2-5 (a 4-point range), it is considered heterogeneous. As the treatment strategy for older patients with MM may be stratified according to frailty status, reliable frailty evaluation is necessary. We aimed to evaluate the potential for further stratifying frail patients using the SFS and its clinical applicability.

Methods:

This study included patients with newly diagnosed MM aged ≥ 70 years who were ineligible for transplantation and were diagnosed between 2012 and 2022. The clinical data of 110 patients treated at Nagoya City University Hospital were used as the training cohort. The validation cohort included 203 patients treated at three affiliated hospitals. The clinical information was retrospectively reviewed. Missing PS data were estimated based on medical records. Overall survival (OS) was estimated using the Kaplan-Meier method and compared using the log-rank test. Univariate and multivariate analyses of OS were performed using Cox proportional hazard models.

Results:

In the training cohort with a median follow-up of 3.5 years (IQR 1.8-6.0), the median age was 76.5 years (range 70-92), with PS ≥2 (32%) and CCI ≥2 (24%). Seventy-two patients were classified as frail (SFS ≥ 2), and their OS was significantly shorter than that of non-frail patients (p = 0.031). Several cutoff points were tested to further stratify frail patients into moderate and severe categories (SFS 2 vs. 3-5, 2-3 vs. 4-5, 2-4 vs. 5). The best stratification was achieved when moderate frailty was defined as SFS 2 or 3. Severe frailty was defined as SFS 4 or 5. The median OS for non-, moderate-, and severe-frailty patients was 7.0, 5.3, and 2.8 years, respectively. Univariate analysis showed hazard ratios (HRs) of 1.74 (95% confidence interval [CI] 0.92-3.3, non- vs. moderate-frail) and 2.38 (95% CI 1.20-4.73, non- vs. severe-frail).

The validity of these cutoff points was evaluated in the validation cohort (median follow-up 2.9 years [IQR 1.8-4.7]), with a median age of 78 years (range 70-98), PS ≥2 (47%), and CCI ≥2 (27%). OS was significantly different when comparing non- vs. moderate-frail (HR 4.88, 95% CI 2.35-10.1) and moderate- vs. severe-frail (HR 13.0, 95% CI 5.17-32.5), demonstrating the validity of our cutoff points of SFS.

Combining the training and validation cohorts, among 290 patients receiving anti-myeloma treatments, unplanned admissions due to adverse events increased with worsening frailty: 28%, 49%, and 62% in the non-, moderate-, and severe-frailty groups, respectively (Cochran-Armitage test, p<0.001). The OS for each frailty status did not significantly differ according to the induction regimen (bortezomib-based vs. lenalidomide-based regimen).

Multivariate analyses showed that the International Staging System (ISS) (I/II vs. III, HR 1.93 [95% CI 1.37-2.72]) and frailty (non-frail vs. moderate-frail, HR 2.88 [95% CI 1.79-4.63]; non-frail vs. severe-frail, HR 6.26 [95% CI 3.69-10.6]) were significant factors for poor OS, whereas elevated LDH levels were not significant. Combining frailty scores (non-, moderate-, and severe-frail as 0, 1, and 2, respectively) and ISS scores (I/II and III as 0 and 1, respectively) more effectively predicted OS risk. Median OS was not reached (NR) (95% CI 7.5 for those with a score of 0, was 4.9 years (95% CI 4.0-5.6) for scores of 1 or 2, and 1.1 years (95% CI 0.4-1.9) for a score of 3.

Conclusion:

The validity of further stratifying frail patients in the SFS into two groups for more accurate prognostic prediction was demonstrated in two independent cohorts. Real-world patients are generally frailer than patients in clinical trials, making this stratified scale particularly valuable in real-world settings. Additionally, this scale can predict severe adverse events and, when combined with ISS, can more accurately predict patient prognosis. Further investigation of the clinical utility of this stratified scale is warranted.

Kato:AbbVie: Honoraria. Suzuki:Sanofi: Honoraria; Janssen Pharmaceutical K.K.: Honoraria; Chugai Pharmaceutical: Honoraria; Amgen: Honoraria; AbbVie: Honoraria; Genmab: Honoraria. Kondo:AbbVie: Honoraria. Kikuchi:Sanofi: Honoraria. Kanamori:Amgen: Honoraria; Janssen Pharmaceutical: Honoraria; Bristol Myers Squibb: Honoraria; Sanofi: Honoraria; Kyowa Kirin: Honoraria; Abbvie: Honoraria; Nipponrinshosha: Honoraria. Yoshida:Bristol Myers Squibb: Honoraria; Janssen Pharmaceutical: Honoraria; Chugai Pharmaceutical: Honoraria; Amgen: Honoraria; Astellas Pharma: Honoraria; Meiji Seika Pharma: Honoraria. Kayukawa:Shionogi & Co., Ltd.: Speakers Bureau; Chugai Pharmaceutical Co., Ltd.: Speakers Bureau; Fujimoto Pharmaceutical Corporation: Speakers Bureau. Sasaki:Sanofi: Honoraria; Asahikasei Pharma: Honoraria; Chugai Pharmaceutical: Honoraria; Janssen: Honoraria. Asano:Bristol-Myers Squibb: Honoraria. Narita:Janssen Pharmaceutical: Honoraria; Chugai Pharmaceutical: Honoraria. Sanda:Amgen: Honoraria; Kyowa Kirin: Honoraria; Astellas: Honoraria. Ri:Bristol-Myers Squibb: Honoraria; Janssen Pharmaceutical: Honoraria; Daiichi Sankyo: Research Funding; Sanofi: Research Funding; Kyowa Kirin: Research Funding. Iida:Abbvie: Consultancy, Research Funding; GlaxoSmithKlein: Consultancy, Research Funding; Otsuka: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Takeda: Honoraria, Research Funding; Ono: Honoraria, Research Funding; Daiichi Sankyo: Research Funding; Shionogi: Research Funding; Alexion: Research Funding; Chugai: Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding.