Selection determines therapeutic effects: a retrospective analysis of the application of different frailty tools in elderly patients with multiple myeloma.

Introduction

Multiple myeloma (MM) is prevalent in middle-aged and older age groups [ 1 ] and has a heterogeneous prognosis. Frailty is a state in which an individual's resistance to stressors decreases and susceptibility increases, and its prevalence increases with age. However, there is no consensus on how to measure frailty. The two most commonly cited methods are fried frailty phenotype and frail scale [ 2 ]. Compared with those in developed countries, the median age of onset of MM in China is earlier (57–58 years) [ 3 , 4 ], but the disease stage is later, and the prognosis is poorer [ 5 – 7 ]; therefore, early identification and early treatment are more necessary. Stratification by frailty assessment tools and individualized treatment are the main measures used to improve the prognosis of MM in elderly individuals [ 8 – 11 ]. Currently, the International Myeloma Working Group Frailty Index (IMWG-FI) is the frailty assessment standard for elderly MM patients recommended by the European Myeloma Network (EMN) guidelines; however, elderly MM patients in China have different characteristics from those of elderly MM patients in Western developed countries, such as large cultural differences and very different life habits [ 12 ], while there are few studies on frailty assessment in China. Therefore, the best assessment model for elderly MM patients in China is still inconclusive, and simpler and more objective assessment modalities need to be explored. In contrast, the UK Myeloma Research Alliance Risk Profile (MRP) score, Mayo score and Intergroupe Francophone du Myélome (IFM) simplified frailty scale are simple and easy to use, and they are the most promising tools for assessing frailty in elderly MM patients in recent years; however, the consistency of the results of these different frailty assessment tools and their validity are still unclear. In this study, 84 newly diagnosed MM patients aged ≥ 60 years in HeBei University Hospital were assessed by these four scales to explore the consistency of the results of different frailty assessment tools and the validity of their stratification.

Patients and methods

General information

Newly diagnosed MM patients aged ≥ 60 years diagnosed in accordance with the IMWG diagnostic criteria and staging (2014 edition), excluding those with amyloidosis, smouldering myeloma and recurrent myeloma, with complete diagnostic and evaluation data were recruited from HeBei University Hospital from From 1 January 2017 to 1 January 2023, and receiving at least 2 courses of chemotherapy. Frailty was assessed before treatment and after every 2 courses. The last follow-up was on May 1, 2023, and the average follow-up time was 40 months.

Frailty assessment tool for older adults

The IMWG-FI[ 13 ] classifies patients into three groups according to age, activities of daily living (ADL) score, instrumental activities of daily living (IADL) score, and Charlson comorbidity index (CCI): fit (score = 0), intermediate fit (score = 1), and frail (score ≥ 2).

The Mayo score[ 14 ] classifies patients into 3 frailty groups [fit (0 points), intermediate fit (1–2 points), and frail (3 points)]according to 3 variables (1 point for each variable): an age ≥ 70 years, an Eastern Cooperative Oncology Group Performance Status (ECOG-PS) ≥ 2, and a serum NT-proBNP level ≥ 300 ng/L.

The MRP [ 15 ] can be used to predict the prognosis of patients with newly diagnosed MM who are not suitable for autologous stem cell transplantation. The score was calculated using the ECOG-PS, MM International Staging System (ISS), age, and C-reactive protein (CRP) level as prognostic variables with the following formula: Score = (ECOG-PS-2) × 0.199 + (age-74.4) × 0.0165 + (ISS-2) × 0.212 + [log(CRP + 1)−2.08)] × 0.0315. The MM patients were divided into three groups: patients with scores < −0. 256 (frail), −0.256 ≤ scores ≤ −0.0283 (intermediate-fit), and scores > −0.0283 (frail). The MRP score was derived based on two clinical studies (the NRCI-XI study and the MRC-IX study) and validated in other external studies, even finding that frailty patients have a higher incidence of adverse effects [ 16 – 18 ].

The IFM [ 17 ] is calculated by incorporating the ECOG-PS score in place of the ADL and IADL questionnaires from the IMWG-FI, and patients were divided into 2 groups: nonfrail (scores < 2) and frail (scores ≥ 2) (Supplementary Materials 1).

Statistical methods

All the statistical analyses were performed using SPSS version 22.0, with the variables and calculations involved in the different frailty instruments as described previously.The IMWG development study showed no significant difference in survival benefit between the fit group and the intermediate-fit group, so fit/intermediate-fit patients in each model were combined as "nonfrail" for he consistency analyses. Normally distributed data are expressed as the mean ± standard deviation (x ± s), and t tests were used for between-group comparisons. Count data are expressed as percentages (%), and χ2 tests were used for rate comparisons. The consistency of the four models and the overlap of frail patients were analysed using cross-tabulations and Cohen's kappa analyses, and survival analysis was performed using the Kaplan‒Meier method. Differences were considered to be significant at P < 0.05.

Results

Baseline characteristics

A total of 84 patients met the eligibility criteria for inclusion in this study, with 19% of them being aged ≥ 75 years and a median age of 68 years (range, 60–84 years). Regarding first-line therapy, 77.4% and 3.6% of the cohort received proteomic inhibitors and immunomodulators (Supplementary Materials 2).The most common comorbidities were hypertension (49.27%),kidney disease(20.29%),diabetes(13.0%).Less frequent comorbidities included other cancers(4.3%),ischemic heart disease(1.4%).Other baseline characteristics are presented in Table 1 and Supplementary Materials 1.

Results of frailty assessment

When the IMWG-FI, Mayo score, MRP and IFM were applied to evaluate the patients, the proportions of patients were as follows: 23 (27.4%), 12 (14.3%), 17 (20.2%), and 27 (32.1%) in the fit group, 16 (19.0%), 52 (61.9%), 28 (33.3%) and 0 patients in the intermediate-fit group, and were 45 (53.6%), 20 (23.8%), 39 (46.4%) and 57 (67.9%) patients in the frail group, respectively (Fig. 1 ). In the subgroup analysis of ≥ 75 years of age, frailty patients identified by the four scores were 75.0%, 56.3%, 81.3%, and 93.8%. There was no statistically significant difference among the different assessment tools in terms of sex, cytogenetics, ECOG-PS, ISS, CCI, CRP level, NT-proBNP level, (Table 2 , P > 0.05).

Consistency among frailty models

The Cohen's kappa coefficients for the IMWG-FI versus MRP and the Mayo score were 0.474 ( P < 0.001) and 0.432 ( P < 0.001), respectively, indicating moderate agreement, whereas the Cohen's kappa coefficients for the IMWG-FI versus IFM, the Mayo score versus MRP, the Mayo score versus IFM score, and the MRP versus IFM had Cohen's kappa coefficients of 0.396 ( P < 0.001), 0.283 ( P = 0.003), 0.218 ( P = 0.003), and 0.350 ( P < 0.001), respectively, which all indicated fair agreement.

Overlap in the categorisation of frail patients

The consistency of the results of the four frailty assessment tools was low, with a total of 64 (76.2%) patients assessed as frail by at least one tool; 48 (75.0%) patients were identified as frail by at least 2 tools, whereas only 14 (21.9%) patients were identified as frail by all 4 tools. Of the 16 frail patients without coidentification, 2, 2, and 12 were identified by the IMWG-FI, MRP, and IFM, respectively. The categorical overlap of the 64 frail patients is shown in Fig. 2 .

Prognostic analyses

When assessed using the IMWG-FI, the median overall survival (OS) was 50.0 and 19.0 months ( P = 0.006), and the median progression-free survival (PFS) was 43.0 and 10.0 months ( P = 0.002) for nonfrail and frail patients, respectively; when assessed using the Mayo score, the median OS was 46.5 and 10.0 months ( P = 0.025), and the median PFS was 20.3 and 7.0 months ( P = 0.006); and when assessed using the MRP, the median OS was 50.0 and 23.0 months ( P = 0.028), and the median PFS was 43.0 and 11.0 months ( P = 0.03). In addition, when assessed using the IFM, the median OS was 46.5 and 26.0 months ( P = 0.598) (Fig. 3 ), and the median PFS was 26.0 and 16.0 months ( P = 0.539) for nonfrail and frail patients, respectively (Fig. 4 ).

The median PFS times of patients assessed as frail by the IMWG-FI, Mayo score, MRP, and IFM were 10.0, 7.0, 11.2, and 16.0 months, respectively ( P = 0.167), whereas the median OS were 19.0, 10.0, 23.0, and 26.0 months, respectively ( P = 0.139) (Fig. 5 ).

Discussion

In the era of new drugs, age and the ECOG-PS are no longer sufficient for describing the heterogeneity of elderly MM patients, and the influence of patients' own prognostics characteristics gradually increases with age, while a relative detriment of the impact of prognostic factors related to tumor biology, such as cytogenetics, can occur.A frailty assessment of a patient's functional status, comorbidities, psychology, and cognition can be used to identify the best treatment options for elderly MM patients and facilitate clinical research in elderly MM patients [ 19 , 20 ]. Comprehensive geriatric assessment (CGA) is now widely used in oncology [ 21 ], and the National Comprehensive Cancer Network (NCCN) guidelines also recommend CGA to assess frailty in patients with malignant haematological diseases. However, CGA is time-consuming and complex and requires a team of specialists, and the disease characteristics of MM itself dictate the need for a specific frailty assessment tool, thus contributing to the development of a frailty tool for MM patients.Although most clinicians believe that routine frailty assessment is time-consuming and costly, research has shown that, in fact, not only is frailty assessment feasible,it is also likely less time-consuming and costly than many other prognostic tests done in oncology [ 22 – 24 ].

The IMWG-FI is the first assessment tool applied to MM patients and was developed in a multicentre retrospective study with a large sample size (n = 869) and external validation [ 25 ]. The score consists of 34 factors and needs to be completed by both the doctor and patient, which is not only cumbersome but also inevitably subjective. In addition, individuals aged ≥ 80 years are directly assigned to the frailty group regardless of their physical status or the presence or absence of comorbidities, which is clearly unreasonable [ 26 , 27 ]. The IFM reduces the subjectivity and complexity of the IMWG-FI by replacing ADL and IADL in the IMWG-FI with the ECOG-PS. However, because the ECOG-PS is a dichotomous variable, it does not reflect the heterogeneity of patient frailty in a dynamic manner [ 28 ]. The Mayo score includes only 3 factors (age, ECOG-PS, and NT-proBNP level) compared with the IMWG-FI, increasing the convenience and objectivity, but the difficulty of standardising NT-proBNP levels across centres limits its clinical application. The MRP, which is mainly based on biochemical and haematological indices, is simpler and easier to use than the other indices and can significantly improve the efficiency of risk stratification in elderly patients. The MRP is based on biochemical and haematological indices and is simple, significantly improves the efficiency and objectivity of risk stratification in elderly patients, and avoids the direct inclusion of patients aged ≥ 80 years into the frail group.

In this study, although the assessment results of the IMWG-FI with the MRP and Mayo score all had moderate concordance, the concordance between the assessment results of any other two tools was moderate, in which only 14 patients (21.8%) were identified as frail by all four tools, which suggests that treatment decisions based on the assessment results of the different frailty tools may result in similar patients receiving different treatments, thus affecting their prognosis and quality of life [ 29 ].

The proportion of frail patients was greater in the present study than in the IMWG-FI development study (53.6% and 30%, respectively) [ 13 ]. This difference may be because the patient cohort in this study was derived from the "real world", including patients with severe renal insufficiency (creatinine level > 2 mg/dl, 46.7% and 5%), an ECOG-PS score of 2–3 (84.4% and 31%), and an ISS score of III (77.8% and 31%), caused by a higher proportion of patients at high cytogenetic risk (46.7% and 24%) (Table 1 ). When comparing the present study with the Mayo score development study [ 14 ], the proportion of frail patients was higher (23.8% and 7%), and analysis of the demographic and baseline characteristics of the two studies revealed that the proportion of patients with an ECOG-PS ≥ 2 (45.0% and 19.0%) and the median NT-proBNP level (1225 ng/L and 109 ng/L) were higher in the present study than in the Mayo development study (Table 1 ). The differences between the two studies may have originated from the inclusion of the ECOG-PS and NT-proBNP level in the Mayo score, and the difficulty in harmonising the criteria for NT-proBNP levels is the main reason for the difficulty in externally validating this score. The proportion of frail patients was consistent when comparing the present study with an external validation study of MRP scores (46.4% and 46.4%) [ 16 ], whereas the proportion of frail patients was greater when comparing the present study with the IMWG-FI development study (67.9% and 49%), which may be related to the fact that the proportion of patients with an ISS of III (77.2% and 38.4%) and ECOG-PS ≥ 2 (40.4% and 21.5%) was greater (Table 1 ).

In this study, the assessment of frailty in patients with a survival period longer than 3 years is not static, and it can either improve or deteriorate over time (Supplementary Materials 3), which is analogous to the conclusion of Mian H et al. [ 30 ], indicating that dynamic assessment is a superior predictor of outcome compared to frailty at diagnosis. Some patients in this study have decided on chemotherapy regimen based on dynamic assessment, but unfortunately, there are few data in this part.

When frailty was assessed using the IMWG-FI, MRP and Mayo score, the median OS (Fig. 3 ) and PFS (Fig. 4 ) were significantly different between the nonfrail group and the frail group[ 25 ]; however, there was no statistically significant difference in the median PFS or OS of patients with frailty assessed by the four models (Fig. 5 ), which suggests that the survival outcomes of the patients who were recognised as frail by the different models were similar in the present study. The efficacy of stratification of the prognosis of the patients by the IMWG-FI, the MRP and the Mayo score was better than that of the IFM. The IMWG-FI is still the geriatric assessment model recommended by the EMN, the European Society for Medical Oncology (ESMO) and other guidelines, and all other frailty models developed need to be compared and validated with the IMWG-FI. In this study, the IMWG-FI showed moderate agreement with the MRP and IFM and only fair agreement with the Mayo score, indicating that the MRP is more effective than the Mayo score and IFM in stratifying patient prognosis. There are fewer prospective studies applying the MRP, Mayo score and IFM scale to guide treatment, and the Myeloma XIV study [FiTNEss, NCT03720041 ] [ 31 ] conducted by the Myeloma UK Consortium used the IMWG-FI; these studies compared the MRP score, which is expected to provide additional evidence-based evidence on the validity of the IMWG-FI and the clinical feasibility of the MRP.

In this study, we found that the assessment results of the four tools varied greatly, and different assessment models may lead to similar patients being assigned to different frailty groups and receiving different treatments; however, the agreement between the MRP score and the IMWG-FI score was high, so combining the IMWG-FI score with the MRP score may reduce the subjectivity of assessment and improve the identification of frailty [ 32 ]. However, given the diverse circumstances of each center, it is advisable to assess frailty in daily clinical practice, and the selection of the score shall rely on the background and experience of each center until a standardized approach can be available. The present study still has limitations. First, the number of patients aged ≥ 80 years included in the study was small to verify whether this conclusion was equally effective in these patients. Second, this was a retrospective study with a small sample size. Fewer patients aged ≥ 80 years were included in the study to verify whether the result was equivalent for these patients. Third, Further analysis is required to examine drug tolerance and the underlying causes of death.Last, since this was a retrospective study with a small sample size, additional randomised controlled studies are needed to validate the findings.

Supplementary Information

Supplementary materials 1 Frailty assessment tools encompass a range of variables.

Supplementary materials 2 First-line treatments and the number（%）.

Supplementary materials 3 Dynamic frailty assessment of 3-year survival patients.

Acknowledgements

The authors thank the patients and their families for contributing to this study

Statement

The study of “Selection determines therapeutic effects：A retrospective analysis of the application of different frailty tools in elderly patients with multiple myeloma” to through the real world data to provide Chinese multiple myeloma patients evidence-based basis, because the study is retrospective study, no adverse effects on participants, but participants to provide medication and physical state data, all participants follow the principle of voluntary and signed informed consent, the researchers in the process of participant information confidential.

Abbreviations

Multiple myeloma

International myeloma working group frailty index

Myeloma research alliance risk profile

Intergroupe francophone du myélome

European myeloma network

Overall survival

Progression-free survival

Activities of daily living

Instrumental activity of daily living

Charlson comorbidity index

Eastern cooperative oncology group performance status

N-terminal pro-brain natriuretic peptide

C-reactive protein

International staging system

Comprehensive geriatric assessment

National comprehensive cancer network

European society for medical oncology

Complete response

Very good partial response

Partial response

Minor response

Stable disease

Author contributions

Conceptualization of the project: YJL,JMX,JW,SYZ,HMG,JBZ and HX;Development of methodology: YJL,SYZ and HX;Management of patients:JMX,JW,SYZ,HMG,JBZ,LYL and HX;Collection, analysis and interpretation of data: YJL,SYZ,JMX,JBZ,LYL and HX;Writing articles and revision of the manuscript: YJL,SYZ and HX.All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Funding

This work was supported by grants from the General Project of Hebei Provincial Department of Finance.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author at xh-xuehua@163.com upon reasonable request. Data is provided within the manuscript or supplementary information files.

Declarations

Ethics approval and consent to participate

The study complied with the Declaration of Helsinki and was approved by the Ethics Committee of Affiliated Hospital of Hebei University.

Competing of interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yujun Li and Songying Zhao have contributed equally as co-first authors.

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Associated Data

Supplementary Materials

Supplementary materials 1 Frailty assessment tools encompass a range of variables.

Supplementary materials 2 First-line treatments and the number（%）.

Supplementary materials 3 Dynamic frailty assessment of 3-year survival patients.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author at xh-xuehua@163.com upon reasonable request. Data is provided within the manuscript or supplementary information files.