Original Paper Optimizing individualized therapy decision-making in multiple myeloma (MM): Integration and impact of the Revised Myeloma Comorbidity Index in the MM-Tumor Board

Original Paper Optimizing individualized therapy decision-making in multiple myeloma (MM): Integration and impact of the Revised Myeloma Comorbidity Index in the MM-Tumor Board | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Original Paper Optimizing individualized therapy decision-making in multiple myeloma (MM): Integration and impact of the Revised Myeloma Comorbidity Index in the MM-Tumor Board Esther Dreyling, Gabriele Ihorst, Heike Reinhardt, Jan Räder, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4432469/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Sep, 2024 Read the published version in Annals of Hematology → Version 1 posted 11 You are reading this latest preprint version Abstract Introduction : Multiple Myeloma (MM) is a hematological disease predominantly affecting elderly patients. The complexity of current treatment necessitates individualized approaches. Therein, functional assessment (FA) tools, such as the Revised Comorbidity Index (R-MCI) at our University- and Comprehensive Cancer Center Freiburg, play a crucial role. This study aimed to determine a) the implementation of the R-MCI in our MM-tumor board (MM-TB), b) its impact on treatment guidance at baseline and c) potential changes during follow-up. Methods : This exploratory study investigated R-MCI coverage and distribution in a cohort of patients with multiple TB presentations. Among them, a follow-up patient cohort undergoing subsequent MM-therapy was analyzed to determine treatment adjustments and changes in patients’ condition measured by R-MCI alterations. Results : During our 3-year assessment period, 565 patients were presented in our MM-TB, totaling 1256 TB-presentations. In the multiple TB presentation cohort, the median number of TB presentations was 3 (range: 2–12). R-MCI scores within the MM-TB were available in 94%, whereas in 6%, the R-MCI had not been integrated. Among these, potential failure to identify the need for treatment modifications was determined. In the follow-up cohort, patient characteristics were typical for referral/university centers. Dose reductions were performed in 55% and were more prevalent among patients with ≥ 4 vs. lesser TB presentations. Most patients (55%) showed a fitness stabilization or improvement via follow-up R-MCI. Conclusion : R-MCI integration in MM-TB exceeded > 90%, indicating its successful integration for treatment support. Our results underscore its value in guiding therapy decisions, providing a comprehensive assessment beyond age considerations. Multiple Myeloma (MM) tumor boards (TBs) Revised Myeloma Comorbidity Index (R-MCI) therapy adjustment geriatric assessment frailty Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Multiple Myeloma (MM) is a hematological disease that predominantly affects elderly patients. The introduction of proteasome inhibitors (PI), immunomodulatory drugs (IMiDs) and immunotherapeutics (monoclonal and bispecific antibodies, antibody drug conjugates, chimeric antigen receptor (CAR)-T-cells), has significantly enlarged therapeutic options and has improved the prognosis, progression-free- (PFS) and overall survival (OS) of MM patients over the last 20 years. 1 Standard treatment for MM now involves triplet or quadruplet therapy which typically includes a combination of a PI, IMiDs, corticosteroid and monoclonal antibody. 2 Additionally, if patients are deemed fit enough, autologous stem cell transplantation (ASCT) followed by maintenance therapy is considered. 2–6 Due to the availability of numerous therapeutic options, treatment of MM has become more complex in recent years, allowing individualized treatment. It is known for example, that carefully selected older patients can benefit from intensive therapy as much as younger patients. These patients may also receive triplets or quadruplets, tolerate longer treatment sequences, and should be included in clinical trials. 2,7–13 However, inclusion of elderly patients over the age of 70 years and of vulnerable individuals in clinical trials is notably infrequent. Consequently, determining the eligibility of individuals for intensive and/or novel treatment can be challenging. 7–14 To identify suitable treatment options for these patients, functional assessment (FA) tools have been established. 7,8,10,13,14 A FA is a multidimensional, multidisciplinary approach to more objectively determine the functional health status of frail, vulnerable and/or elderly patients. 7–14 Recently, MM-specific risk scores, such as the International Myeloma Working Group (IMWG)-frailty score, Revised-Myeloma Comorbidity Index (R-MCI), Mayo-risk score, and UK Myeloma Research Alliance Risk Profile, were compared using retrospective (test analysis) and prospective data (validation) to assess, whether they yield similar results. Moreover, FA is already utilized to guide therapeutic management. 10,13,14 However, in routine clinical practice, these tools are currently assessed and considered in only about 20% of myeloma patients, and the consistent integration of FA into MM-tumorboards (MM-TBs) for therapeutic decision-making has not been evaluated. 7–14 At our Comprehensive Cancer Center Freiburg (CCCF), FA is conducted via the R-MCI. This validated MM-specific risk score can also be reliably conducted using retrospective data 14 and is consistently assessed in our MM patients before treatment initiation. Furthermore, it has been integrated into our electronic Tumorboard online system (TOS). 7–10,13,14 The R-MCI web tool enables the immediate calculation of the R-MCI ( www.myelomacomorbidityindex.org 15 ) for physicians, study nurses and research assistants. As FA, exemplified by the use of the R-MCI in MM-TB, and multidisciplinary care are novel standards in improving patient outcomes by finding the fine line between under- and overtreatment, 8,9,16 the aim of this study was to determine a) the extend and the reliability of the integration of the R-MCI in our MM-TB, b) its impact on treatment guidance at baseline and c) R-MCI changes during follow-up in consecutive MM patients at our center. Material and methods Data sources and study design We performed this exploratory study in consecutive MM patients who were presented in our MM-TB at the CCCF, as described previously. 9,16 All patient information was recorded in the electronic documentation system, Medoc, and retrieved from it. 7,10,13,14,16 Patient dispositions are outlined in Fig. 1: we retrieved 565 MM patients (100%) with 1256 MM-TB presentations (100%), being presented and discussed either once or repeatedly between February 2018 and June 2021. To maximize the use of prospective and unbiased data for the follow-up, we focused on patients with a minimum of two MM-TB presentations, anticipating at least two R-MCI assessments/patient (marked in light blue in Fig. 1: n=215 patients). This formed a cohort of 215 MM patients with multiple TB presentations (n=691), in which we evaluated the R-MCI data and number of MM-TB presentations/patient (2, 3, 4, 5, 6, 7, ≥8). Out of these 215 patients, 179 patients with 603 MM-TB presentations underwent prospectively performed R-MCI assessments and subsequent anti-myeloma-therapy. Follow-up R-MCI calculations were available for 130 of these patients (with 485 MM-TB presentations; marked in red in Fig. 1). This ‘follow-up cohort’ was analyzed for patient characteristics which included age, MM staging, number of therapy lines at MM-TB assessment and therapy data (induction, maintenance or subsequent MM therapy). The aim of this study was to determine a) the extend and the reliability of the integration of the R-MCI in our MM-TB, b) its impact on treatment guidance at baseline [a) and b) performed in cohort of 215 MM patients with multiple TB presentations (n=691), marked in light blue in Fig. 1] and c) R-MCI changes during follow-up in consecutive MM patients at our center (n=130 patients, with 485 TB presentations, marked in red in Fig. 1). Moreover, we compared therapy intensity (dose reductions done vs. not) in subgroups of patients, categorized by frailty (R-MCI: fit, intermediate-fit, frail) vs. age (<60, 60-69, ≥70 years) in analogy to Holler et al. 10 The study was performed according to the guidelines of the Declaration of Helsinki and Good Clinical Practice. All patients gave their written informed consent for institutionally initiated research studies and analyses of clinical outcome studies conforming to the institutional review board guidelines. The ethics committee of the University of Freiburg (UKF) approved the trial protocol (EV, 81/10 + 22-1491-S1). R-MCI assessment The R-MCI comprises five weighted risk factors, namely renal and lung function, Karnofsky performance status (KPS), frailty and age. Additionally, it allows to include cytogenetics (CGs) if available. 7,8 Since the R-MCI had been integrated into our TOS at our UKF center to be readily available for patient- and fitness-related questions, we assessed its extent of coverage within the MM-TB. In cases, where the R-MCI had not been found integrated within the MM-TB (Fig. 3; 6%), we used the online R-MCI calculator (www.myelomacomorbidityindex.org 15 ) to determine the R-MCI retrospectively, as descibed. 14 Dose reductions and follow-up analysis Our aim was to examine the impact of the R-MCI on therapy decisions, analogous to prior reports. 10,13 Therefore, we focused on patients who were initiated on anti-MM therapy after initial R-MCI assessment. We defined a shorter time span as compared to prior studies 10,13 , here of a maximum of 6 months between the R-MCI assessment and subsequent therapeutic decision to assess the possible impact of R-MCI changes within shorter time frames. Dose reduction was defined according to dose reduction recommendations in UKF/CCCF therapy handbooks and chemotherapy schedules 17,18 as described. 10 Decisions of dose reductions were based on physicians’ choices, 10,13 but these were here influenced by TOS-integrated R-MCI data. This was different to previous data by Holler et al., where the R-MCI had not been obligatory to insert into our TOS-MM-TB. 10 In 43 TB presentations (6%), the R-MCI had not been prospectively inserted into our TOS-MM-TB, thus was therein unassessed for the MM-TB discussion. In these cases, two physicians (ED+ME), both trained in onco-geriatrics, independently determined, whether chosen MM-decisions and given therapy suggestion would have been different, if the R-MCI had been assessed before therapy initiation (Fig. 4). Through these data, we could determine, whether therapy intensity aligned with the fitness levels determined via R-MCI, providing full dose for fit patients and reduced intensity for frail patients. To further assess the therapy decisions, we examined whether patients’ constitution had changed in a follow-up analysis. Therefore, we evaluated the specific distribution of patients among R-MCI scores before start of therapy (T0) and follow-up (T1; Table 4). We also assessed the R-MCI changes over time, namely whether the R-MCI improved, remained unchanged or deteriorated (Fig. 5), in line with previous studies. 10,13 Statistical analysis The trial was analyzed descriptively, providing means, median and range for continuous measures, and absolute and relative frequencies for categorical variables. The R-MCI was assessed and compared in age subgroups of <60-, 60-69- and ≥70-year-old patients, in analogy to prior analyses 10,13 (Tables 2+3), as well as at initial and subsequent (=follow-up) assessment (Table 4). Data were assessed using GraphPadPrism V5.03 and SAS 9.4 (SAS Institute Inc. USA) and were analyzed as of 1/2023. Results Number of MM-TB presentations per patient For patients with ≥2 MM-TB presentations (n=215, Fig. 1), we assessed the median TB-presentations/patient, which were three within our 3-year assessment period (2/2018 – 6/2021), in line with prior analyses of our group (Fig. 2). 9,16,19 Fig. 2 displays the number and frequencies of patients with repeated (2, 3, 4, 5, 6, 7 or ≥8) TB presentations. Within the 3-year study, most patients were presented within our MM-TB 2 or 3 times (71%), ≥4 presentations were found in 29% of patients and ≥6 presentations/patient were rare (9%, Fig. 2). R-MCI adherence at the MM-TB and prospectively vs. retrospectively assessed R-MCI Within 691 MM-TBs (Fig. 1+2), prospective R-MCI scores were available in 94% (648/691 MM-TB protocols, Fig. 3). In the remaining 6% of presentations (n=43), the R-MCI was calculated retrospectively. Regarding the R-MCI subgroups of the prospectively assessed scores, 30% patients were classified as fit (R-MCI 0-3), 52% as intermediate-fit (R-MCI 5-6) and 18% as frail (R-MCI 7-9) in line with prior analyses (Fig. 3, left column). 7,9,10,13,16 In the few retrospectively scored presentations, fit, intermediate and frail patients were observed in 16%, 58% and 26%, respectively (Fig. 3, right column). Thus, patients with non-included R-MCI assessment within the MM-TB TOS seemed 1.9-fold less fit (30%→16%) and 1.1-fold more intermediate-fit (52%%→58%) or 1.4-fold frailer (18%→26%) as compared to the prospectively evaluated cohort (Fig. 3). Differences in therapy decisions without prospective R-MCI assessment In 43 MM-TB presentations (6%), the R-MCI had not been utilized to aid the TB decision (Fig. 3). In 40 cases (93%), the MM-TB decisions (reassessed by ED+ME) were not found to have been chosen differently (Fig. 4). However, in three patients, both physicians (ED+ME) would have modified treatment according to the R-MCI. Notably, all three were frail according to the R-MCI, including the only <60-year-old patient with an R-MCI of 7/9. The first 78-year-old male patient had received dose-reduced bortezomib-cyclophosphamide-dexamethasone (VCd), although, due to his R-MCI of 9/9 (=utmost frailty), Vd might have been more appropriate retrospectively. The second 79-year-old female patient with an R-MCI of 8/9 had received rituximab-bortezomib-dexamethasone treatment due to high CD20 plasma cell expression, where best supportive care (BSC) would have been more appropriate retrospectively. The third 53-year old male patient with an R-MCI of 7/9 had received Daratumumab-Vd (DVd, adapted according to the Alcyone study 20 ) and was initially intended to undergo ASCT due to his age. Retrospectively, the therapeutic choice would have been DVd alone. Thus, the outcome (progressive disease in 3/3, subsequent hospitalization in 3/3 and substantial dose reduction being necessary in 2/3 and BSC in 1/3) of all three frail patients suggested that better therapy choices could have been made, if the R-MCI had been utilized to aid in the therapeutic process. Notably, MM-related death occurred in 2/3 patients. Patient characteristics We focused on 130 patients with ≥2 MM-TB presentations/patient (with 485 MM-TB presentations), subsequent anti-MM treatment and R-MCI follow-up assessment (Fig. 1 + Table 1). Their median age of 66 years (range 38-86) at initial presentation was typical for referral and university centers, with 62% being male and 38% female. Expectedly, the most common paraprotein types were IgG and kappa light-chains in 56% and 71%, respectively (Table 1). Advanced ISS stage (2 or 3) was frequent with 68%. During the observation period, a median of two therapy lines/patient (range 1-9) had been performed, with induction, maintenance, and later-line (relapse) therapy being performed in 31%, 17% and 52%, respectively. Age subgroups and further analysis of the distribution of R-MCI scores within their groups Age subgroups of patients <60, 60-69 and ≥70 years were equally distributed with 34%, 30% and 36%, respectively (Table 2). Expectedly, younger patients aged <60-years were mostly fit (64%) or intermediate-fit (34%), while frail patients were rare (2%). In the group of 60-69-year-old patients, a substantial shift from fewer fit (33%) to more intermediate-fit (54%) and frail patients (13%) was noted. Even more strikingly, however, 9% of ≥70-years-old patients were classified as fit, whereas most (55%) were intermediate-fit, and 36% were frail (Table 2). Thus, being fit was 4.5-times more prevalent in elderly patients than frailty in young patients. Patient- and therapy-relevant differences in entire cohort and R-MCI and age subgroups Differences in patient frequencies, median age and dose reduction in the entire patient group, as well as in R-MCI vs. age subgroups are summarized in Table 3. While dose reduction in the entire patient group occurred frequently (55%), this was less common in R-MCI fit patients (38%), and increased in intermediate-fit and frail patients to 61% and 74%, respectively. Notably, dose reduction in <60-, 60-69- and ≥70-year-old patients were performed in 45%, 49% and 70%, respectively. Thus, dose reduction was less common in fit patients than in <60-year-old patients. Conversely, in intermediate-fit and frail patients, dose reduction occurred more frequently than in 60-69- and ≥70-year-old patients (Table 3). R-MCI changes before start of therapy (T0) vs. follow-up (T1; serial R-MCI assessment) Serial R-MCI assessments were available for 130 patients within 485 MM-TB presentations and with anti-MM therapy being performed (Fig. 1). Our follow-up assessment of potential R-MCI changes was here conducted earlier than in previous analyses (after a median of 5 rather than previously after 11 months). 10,13 The mean and median R-MCI at T0 were 4.3 and 4 (intermediate-fit) and at T1 4.7 and 5 (remaining intermediate-fit), respectively (Table 4). The precise distribution of patients among R-MCI scores at T0 and T1 is displayed in Table 4. Notably, over the median follow-up period of 5 months (range: 0-25), the number of fit patients slightly decreased (T0: 34.6% → T1: 27%), while the number of intermediate-fit patients increased (T0: 47.7% → T1: 56%), and the number of frail patients remained stable (T0: 17.7% → T1: 17%). Additionally, we assessed in all patients, whether their constitution via R-MCI changed within our follow-up period: in 55%, this improved or remained unchanged, whereas in 45%, a decline was noted (Fig. 5). Dose reduction in relation to number of MM-TB presentations In terms of dose reduction, we also analyzed, whether frequencies of dose reduction were related to the number of TB presentations/patient, namely, whether with lesser vs. more frequent TB discussions, dose-reductions increased due to MM patients’ quality of life (QoL) decreasing with subsequent treatment lines, as described previously (Fig. 6). 21 In patients with 2 or 3 TB-presentations, no dose reduction vs. dose reduction were performed in similar frequencies with 51% and 49%, respectively. This was different in patients with more advanced or difficult-to-treat MM showing ≥4 TB-presentations: no dose reduction was here performed in only 36%, whereas dose reduction was much more frequent in 64% (Fig. 6). The frequencies of no dose reduction vs. dose reduction in each subsequent 2 to ≥8 TB frequencies are outlined in Suppl. Fig. 1. Discussion Since therapy decision-making is ideally supported by FA to individualize treatment especially for frail patients, we integrated the R-MCI into our MM-TB. 9 This integration allows all users to readily distinguish fit from frail patients and expeditiously adjust therapy intensity during our weekly performed interdisciplinary MM-TB discussion. 9,10,13,14 While various functional tests, including different comorbidity scores and geriatric functional tests have been examined, 13,27–30 the R-MCI was explicitly helpful to individualize treatment decisions and improving the tolerance of MM therapy. 10 Additionally, the R-MCI has been recognized as the only comorbidity index that did not show significant differences in risk group distribution for both retrospective and prospective data, thus it was reliably assessable from both data sets. 14 Another convenience is the user-friendly R-MCI homepage ( www.myelomacomorbidityindex.org 15 ). While fitness assessments are used for tailoring therapy in other hematological diseases, these are not routinely established in MM patients, despite studies aiming to elucidate their usefulness. 10,13,31 FA have been described as challenging to integrate into everyday clinics due to time constraints. 13,32–34 The pivotal outcome of our study was the successful integration of the R-MCI into MM-TB protocols in > 90%, confirming previous studies of the R-MCI being resourceful. 7–10,13,14,24,33 The establishment of the R-MCI in our MM-TB exemplified that frailty scores can be readily used in everyday clinics. Albeit the R-MCI calculation is specifically requested in our TOS MM-TB system, its use and integration for each patient therein was not obligatory within TOS during the assessment period, therefore the availability in > 90% of our large MM-TB cohort (n = 691 MM-TB cases; Fig. 1 ) was a success. Of note, the R-MCI was unavailable in 43 patients (6%) only, who had been externally referred to our UKF/CCCF: either missing data were reasons for its non-use, or physicians from different disciplines/departments were overriding the TOS-integrated R-MCI scoring. In these patients, the subjective assessment of the introducing physicians within the MM-TB sessions was utilized (which would have otherwise been complemented by the R-MCI). Meanwhile, we have improved the TOS MM-TB software to make it mandatory to enter the R-MCI parameters required for its calculation and thereby ensuring that R-MCI scores are available in 100% of patients. Consistent with previous analyses, we affirmed the rarity (2%) of frailty in < 60-year-old patients but acknowledged its significance. This was indeed important to determine, because in the only frail 53-year-old patient, CD38-based induction and ASCT had been the TB-recommendation, whereas CD38-based therapy alone would have been the better TB-choice according to the R-MCI assessment. We observed an increase in frailty to 36% in ≥ 70-year-old patients, albeit among them also 9% were fit and 55% were intermediate-fit. Dose reduction was performed in alignment with fitness levels in 38% in fit, 61% in intermediate-fit and 74% in frail patients. Decision-making without an available R-MCI revealed that in three frail patients, therapeutic decision could have been facilitated with exact knowledge of patients’ fitness. Consequently, therapy choices would have differed, if the R-MCI had been assessed before therapy initiation. Of note in this study and different to others 10,13 was, that our follow-up assessment of potential R-MCI changes was conducted earlier, after a median of 5 months, and that the R-MCI showed fitness improvement or stability in 55%, while a decline was observed in 45% of cases. In previous studies, where the follow-up was conducted after a median of 11 months, the R-MCI showed rather an improvement in 90% of patients than decline in only 10%. 10,13 This indicates that it may be more advisable to evaluate changes in fitness and quality of life (QoL) after a longer period following the initiation of therapy, in order to prevent temporary therapy side effects from affecting QoL. 10,13,21,35 Therefore, to possibly better capture MM patients’ advances in performance, therapy endurance and QoL, a defined latency of approximately 1 year appears more suitable than < 6 months. Likewise, the common practice of repeatedly assessing QoL domains (i.e. in QoL questionnaires in clinical studies) over very short periods may be less practical in view of our data. 10,13,21,35 Our assessment of the MM-TB over a 3-year period revealed that 38% of patients were presented at least twice, resulting in at total of 691 MM-TB presentations. Among these patients, 71% had 2–3 MM-TB presentations within our observation period, while 29% had ≥ 4 presentations, and 9% had ≥ 6, supporting our view on very frequent TBs. 19 MM-TB outcome data of 2020/21 − 9 and 2012-2014-analyses 16 as well as our data here seem valuable, as we had previously described the postulated survival benefit in patients with ≥ 3 TB discussions as error-prone, occurring due to an immortal time bias (since patients need to survive long enough to be discussed more often). Therefore, time-biased results should not lead to the conclusion that more TBs will increase patients' survival. Instead, insightful discussions within one or few meaningful, long-lasting TBs, ideally in interdisciplinary teams, will generate most profound results for cancer patients. 19,36 Of interest was, that the number of dose-reduced therapies in our entire cohort was higher than in previous studies (55% vs 41% 10 , respectively). This difference was likely related to our focus on MM-TB-patients, whereas Holler et al. had assessed physician-based therapeutic decisions of consecutive MM patients. 10 Our results revealed that dose adaptions were regularly performed in frail patients. Although age-based dose reduction was also observed, they seemed more error-prone than if the R-MCI was included in the decision-making: older patients (≥ 70 years) were treated with dose reduction in 70%, albeit only 36% of them were frail, while 9% were fit and 55% were intermediate-fit. Consequently, this group of patients was rather undertreated in substantial numbers, as previously described. 8 In line, younger patients can be frail and are important to decipher likewise. Therefore, the assumption that younger patients should always receive full-dose treatment, and elderly patients should not, may often be error-prone. This confirms that age alone is not sufficient to determine patients’ health status and therapy endurance. Instead, FA is superior in specifying patients’ constitution and biological age 7–14,24 which is why treatment decisions should rather depend on FA tools, such as R-MCI or others. 12,23,24,27–30 Strengths of our analysis included the precise examination of a large MM-TB cohort, the repeated R-MCI analysis, and the observed dose reduction, well-associated with R-MCI-, rather than age-subgroups. Our observation period of 3 years was substantial, and the detailed examination of patients with various numbers of TB presentations and deterioration in their health status (R-MCI) exhibited their complexity. This is in line with a prior analysis in MM patients with first- vs. later lines of therapy as compared to BSC, 21 which, however, did not assess QoL changes - as here - in consecutive but different follow-up cohorts. Our analysis was well comparable to prior analyses 9,16,19 and revealed the quality of one out of 24 TBs at our UKF/CCCF: while the quality results of our MM-TB, the decisions, pathway- and guideline-adherence, TB-compliance, referrer satisfaction, and improvement of clinical trial inclusion have been described previously, 9,16,19 our data here proved that FA integrated into TBs is feasible and does support therapy decisions. Limitations of the study were the single-institution approach and the range of patients’ ages (38–86 years), with 64% of patients being < 70 years old. This is, however, typical for MM patients in tertiary centers and suggests that our data are even more relevant in older patients. Additionally, the specific conditions for our study inclusion (MM-TB presentations ≥ 2, subsequent therapy being instituted, and performed follow-up R-MCI) focused on more complex MM patients (and a subset of our initial study cohort, Fig. 1 ). Our cohort did include patients receiving different treatment with induction, maintenance and later-line treatment, since our aim was not survival analyses, rather than to assess the completeness of the R-MCI within our MM-TB, whether therapy decisions in terms of fitness vs. age cohorts were different and how dose-reductions were performed. The aim of this study was therefore not to determine exact therapy choices of newly diagnosed MM vs. relapsed/refractory MM, or within different therapy lines, nor whether patients did profit from dose-reductions, because we and others had shown this in prior publications. 7,8,10,27–30,37–44 Moreover, our follow-up assessment was conducted within a relatively short period which should ideally be performed after ~ 1 year, according to Scheubeck and Holler. 10,13 Another criticism may arise from the retrospective evaluation of three patients (whose R-MCI was unavailable in TOS and who received different, more intensive treatment due to the unavailability of their R-MCI). This introduced bias as their outcome was known during our reassessment of therapy choices. Last, since we had examined survival repeatedly in similar MM cohorts, via R-MCI and age subgroups and in different MM-TB cohorts, 7–10,13,14,16 this was not repeated here. In conclusion, our results demonstrate the widespread use of the R-MCI within the MM-TB. Further research through prospective clinical trials seems essential to determine optimal, personalized treatment options for each patient. Building on this approach, Mian et al. published a systematic review including 43 clinical trials considering frailty tools and showed an encouraging trend to incorporate frailty assessments in clinical evaluations and treatment decisions, 41 in line with our data of the R-MCI-integration in TOS-MM-TBs in > 90%. The association between the R-MCI and chosen therapy intensity was better than via age cohorts, which further underlines that the R-MCI is a more precise predictor than age alone. We could show that the recommendations to establish therapy decisions on FA can be directly implemented in TBs. Therapy decisions for intermediate-fit patients appear more complex than for fit and frail patients, because some intermediate-fit patients may endure full-dose treatment, while others need dose-reduction. Therefore, this group of patients should be analyzed further. Today, some MM experts distinguish only two groups of fit vs. frail patients. 6,10,38 Prospective studies using the R-MCI as an important tool for therapeutic decision-making are in process at our CCCF. Most importantly, these and other important TB analyses have led to our better interpretation of cancer care, in close collaboration with statisticians 16,22,45–47 , which is essential to produce reliable evidence for future progress. We are grateful that these productive collaborations continue to exist at our and other CCCs. Declarations Acknowledgements : The authors thank DSMM, GMMG, EMN and IMWG experts for their support and prior recommendations on this study. We thank all MM patients who participated in this study and the entire MM-TB, especially Drs. Henning Schäfer (radiation oncology), PD Jakob Neubauer (radiation department), Marc-Antoine Calba (pathology), Daniel Textor, Jan Barleben and Cornelius Struck (CCCF Tumorboard Online System (TOS)), Mandy-Deborah Möller (sport support group), Johannes Jung (TUR München), Johannes Waldschmidt (Würzburg), Cornelius Miething, and Michael Rassner (all others UKF), for their inspirations, dedication and thrive to achieve best results for our MM patients. The results were presented in part at the 'German, Austrian and Swiss annual Hematology & Oncology meetings' (DGHO), MM workshop meetings in Freiburg and Saig Med1 retreat meetings. Statement of Ethics: (EV EK 22-1491-S1) Data Availability: The data that support the findings of this study are available from the corresponding author (ME) upon reasonable request . Competing Interests : All authors have no conflicts of interest regarding the content. Funding Sources: No funders to declare. Author Contributions : ME, RW and GI designed the research, ED, ME, and GI performed the analysis, analyzed the results and prepared tables and figures. ED and ME wrote the original draft of the paper. RW, GI, JR, HR, MH, GH and CG critically reviewed and edited the paper. All authors approved the final version of the paper. References Stadtmauer EA (2024) Antibody-Based Therapy for Transplantation-Eligible Patients with Multiple Myeloma. N Engl J Med 390(4):368–369 Sonneveld P, Dimopoulos MA, Boccadoro M et al (2024) Daratumumab, Bortezomib, Lenalidomide, and Dexamethasone for Multiple Myeloma. 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Blood Cancer J 13(1):6 Larocca A, Dold SM, Zweegman S et al (2018) Patient-centered practice in elderly myeloma patients: an overview and consensus from the European Myeloma Network (EMN). Leukemia 32(8):1697–1712 Scheubeck S, Ihorst G, Schoeller K et al (2021) Comparison of the prognostic significance of 5 comorbidity scores and 12 functional tests in a prospective multiple myeloma patient cohort. Cancer 127(18):3422–3436 Schoeller K, Ihorst G, Reinhardt H et al (2023) Comorbidity indices for prognostic evaluation in multiple myeloma: a comprehensive evaluation of the Revised Myeloma Comorbidity Index and other comorbidity indices with pro- and retrospective applications. Haematologica Engelhardt M, Dold SM, Ihorst G, Knaus J, Schumacher M (2015) R-MCI webpage Engelhardt M, Selder R, Pandurevic M et al (2017) [Multidisciplinary Tumor Boards: Facts and Satisfaction Analysis of an Indispensable Comprehensive Cancer Center Instrument]. 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Lancet Healthy Longev 3(9):e628–e635 Patel BG, Luo S, Wildes TM, Sanfilippo KM (2020) Frailty in Older Adults With Multiple Myeloma: A Study of US Veterans. JCO Clin Cancer Inf 4:117–127 de la Rubia J, González B, Cruz-Jentoft AJ et al (2023) Geriatric assessment in hematology scale predicts treatment tolerability in older patients diagnosed with hematological malignancies: The RETROGAH study. J Geriatr Oncol 14(1):101401 Jensen CE, Deal AM, Nyrop KA et al (2024) Geriatric assessment-guided interventions for older adults with multiple myeloma: A feasibility and acceptability study. J Geriatr Oncol 15(2):101680 Eichhorst B, Hallek M, Goede V (2018) Management of unfit elderly patients with chronic lymphocytic leukemia. Eur J Intern Med 58:7–13 Wildes TM, Tuchman SA, Klepin HD et al (2019) Geriatric Assessment in Older Adults with Multiple Myeloma. J Am Geriatr Soc 67(5):987–991 Mian H, Brouwers M, Kouroukis CT, Wildes TM (2019) Comparison of Frailty Scores in Newly Diagnosed Patients with Multiple Myeloma: A Review. J Frailty Aging 8(4):215–221 Jensen CE, Vohra SN, Nyrop KA et al (2022) Physical Function, Psychosocial Status, and Symptom Burden Among Adults with Plasma Cell Disorders and Associations with Quality of Life. Oncologist 27(8):694–702 Greil C, Engelhardt M, Ihorst G et al (2019) Allogeneic transplantation of multiple myeloma patients may allow long-term survival in carefully selected patients with acceptable toxicity and preserved quality of life. Haematologica 104(2):370–379 Freytag M, Herrlinger U, Hauser S et al (2020) Higher number of multidisciplinary tumor board meetings per case leads to improved clinical outcome. BMC Cancer 20(1):355 Waldschmidt JM, Keller A, Ihorst G et al (2018) Safety and efficacy of vorinostat, bortezomib, doxorubicin and dexamethasone in a phase I/II study for relapsed or refractory multiple myeloma (VERUMM study: vorinostat in elderly, relapsed and unfit multiple myeloma). Haematologica 103(10):e473–e479 Facon T, Dimopoulos MA, Meuleman N et al (2020) A simplified frailty scale predicts outcomes in transplant-ineligible patients with newly diagnosed multiple myeloma treated in the FIRST (MM-020) trial. Leukemia 34(1):224–233 Facon T, Cook G, Usmani SZ et al (2022) Daratumumab plus lenalidomide and dexamethasone in transplant-ineligible newly diagnosed multiple myeloma: frailty subgroup analysis of MAIA. Leukemia 36(4):1066–1077 Larocca A, Bonello F, Gaidano G et al (2021) Dose/schedule-adjusted Rd-R vs continuous Rd for elderly, intermediate-fit patients with newly diagnosed multiple myeloma. Blood 137(22):3027–3036 Mian H, McCurdy A, Giri S et al (2023) The prevalence and outcomes of frail older adults in clinical trials in multiple myeloma: A systematic review. Blood Cancer J 13(1):1–13 Rosko AE, Huang Y, Benson DM et al (2019) Use of a comprehensive frailty assessment to predict morbidity in patients with multiple myeloma undergoing transplant. J Geriatr Oncol 10(3):479–485 Mina R, Bringhen S, Wildes TM, Zweegman S, Rosko AE (2019) Approach to the Older Adult With Multiple Myeloma. Am Soc Clin Oncol Educ Book Am Soc Clin Oncol Annu Meet 39:500–518 Coulson AB, Royle K-L, Pawlyn C et al (2022) Frailty-adjusted therapy in Transplant Non-Eligible patients with newly diagnosed Multiple Myeloma (FiTNEss (UK-MRA Myeloma XIV Trial)): a study protocol for a randomised phase III trial. BMJ Open 12(6):e056147 Anderson JR, Cain KC, Gelber RD (2008) Analysis of survival by tumor response and other comparisons of time-to-event by outcome variables. J Clin Oncol Off J Am Soc Clin Oncol 26(24):3913–3915 Ihorst G, Waldschmidt J, Schumacher M, Wäsch R, Engelhardt M (2015) Analysis of survival by tumor response: have we learnt any better? Ann Hematol 94(9):1615–1616 Dold SM, Möller M-D, Ihorst G et al (2021) Validation of the revised myeloma comorbidity index and other comorbidity scores in a multicenter German study group multiple myeloma trial. Haematologica 106(3):875–880 Tables Table 1. Characteristics of actively treated MM patients with follow-up R-MCI assessment (n=130) Variables Number of patients (%) Median (range) Age at therapy initiation 66 (38-86) Males : females 81 (62) : 49 (38) MM type IgG / IgA / IgM / biclonal / LC only Kappa / lambda / biclonal AL-Amyloidosis 73 (56) / 20 (15) / 2 (2) / 2 (2) / 33 (25) 92 (71) / 36 (28) / 2 (1) 3 (2) ISS stage I / II / III 39 (32) / 37 (30) / 47 (38) Therapy lines @ MM-TB assessment 2 (1-9) Induction (first-line) MM therapy Under maintenance therapy Subsequent (later line) MM therapy 40 (31) 22 (17) 68 (52) Abbreviations: MM: multiple myeloma; ISS: international staging system; @: at Table 2. Distribution of age subgroups and within their group the number and proportion fit, intermediate-fit and frail patients via R-MCI (n=130) R-MCI subgroup Age subgroups Entire group Fit Intermediate-fit Frail <60 years (%) 44 (34) 28 (64) 15 (34) 1 (2) 60-69 years (%) 39 (30) 13 (33) 21 (54) 5 (13) ≥ 70 years (%) 47 (36) 4 (9) 26 (55) 17 (36) Table 3. Patient- and therapy-relevant differences in entire and R-MCI- vs. age subgroups in frequencies, age and treatment performed without (w/o) vs. with (w) dose reduction Entire group R-MCI subgroups Age subgroups Fit Intermediate Frail <60 years 60-69 years ≥ 70 years Patients (%) 130 (100) 45 (34) 62 (48) 23 (18) 44 (34) 39 (30) 47 (36) Median age (range) 66 (38-86) 58 (38-78) 68 (48-84) 77 (72-86) 55 (38-59) 65 (60-69) 77 (70-86) Patients w/o dose reduction (%) / w dose reduction (%) 58 (45) / 72 (55) 28 (62) / 17 (38) 24 (39) / 36 (61) 6 (26) / 17 (74) 24 (55) / 20 (45) 20 (51) / 19 (49) 14 (30) / 33 (70) Abbreviations: intermediate: intermediate-fit, w/o: without, w: with Table 4. Comparison of R-MCI at T0 versus T1 with number of patients and Mean / Median (range) values R-MCI subgroups R-MCI 0-9 (n=130) T0 = initial assessment (# of patients) T1 = follow-up assessment (# of patients) 0 2 2 1 6 2 Fit 2 18 10 3 19 (0-3: n=45=34.6%) 21 (0-3: n=35=27%) 4 26 27 Intermediate-fit 5 24 27 6 12 (4-6: n=62=47.7%) 19 (4-6: n=73=56%) 7 16 15 Frail 8 7 6 9 0 (7-9: n=23=17.7%) 1 (7-9: n=22=17%) Mean / Median (range) 4.3 / 4 (0-8) 4.7 / 5 (0-9) Abbreviations: T0: initial R-MCI assessment before treatment initiation, T1: follow-up assessment of potential R-MCI changes after treatment and median follow-up of 5 months Additional Declarations No competing interests reported. Supplementary Files 2bSuppl.Fig.1.docx Supplementary Figure 1. Comparison of patients without dose reduction (blue) vs. with dose reduction (yellow) in 2 to ≥8 MM-TBs (n=130 patients in 485 MM-TBs) Cite Share Download PDF Status: Published Journal Publication published 21 Sep, 2024 Read the published version in Annals of Hematology → Version 1 posted Editorial decision: Revision requested 23 Aug, 2024 Reviews received at journal 23 Aug, 2024 Reviewers agreed at journal 23 Aug, 2024 Reviewers agreed at journal 20 Aug, 2024 Reviews received at journal 22 Jul, 2024 Reviewers agreed at journal 09 Jul, 2024 Reviewers agreed at journal 29 Jun, 2024 Reviewers invited by journal 27 May, 2024 Submission checks completed at journal 24 May, 2024 Editor assigned by journal 24 May, 2024 First submitted to journal 16 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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(Flow-Diagram)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/4c707f52a3921ee0868451c7.png"},{"id":58077699,"identity":"65bad8ac-a5ba-4e57-a4c3-1e46fc74d91e","added_by":"auto","created_at":"2024-06-10 22:40:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62014,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of MM-TB presentations \u003cu\u003e\u0026gt;\u003c/u\u003e2, allowing follow-up assessments as the requisite of study inclusion (n=691 MM-TBs)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/517489f3ffae85042aafdc8a.png"},{"id":58077286,"identity":"a7807d7d-4b1b-4bb2-8fe9-48737ea26c37","added_by":"auto","created_at":"2024-06-10 22:32:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79708,"visible":true,"origin":"","legend":"\u003cp\u003eR-MCI distribution of 215 repeatedly presented MM-TB patients in 691 MM-TB presentations, prospectively vs. retrospectively scored\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/6fd6d8a1c0656b0517366840.png"},{"id":58077701,"identity":"217f9926-1829-493f-8c4e-c4eb96ac2250","added_by":"auto","created_at":"2024-06-10 22:40:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":188347,"visible":true,"origin":"","legend":"\u003cp\u003eClinical reassessment in MM patients, where R-MCI had not been scored prospectively, but was retrospectively assessed\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/8b45a2e1782081bef16f53c9.png"},{"id":58077288,"identity":"caadf302-ecea-466c-8219-52be9d9deef2","added_by":"auto","created_at":"2024-06-10 22:32:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":25516,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of R-MCI scores at initial vs. follow-up assessment (n=130 patients with 485 MM-TBs)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/b8277a51d8123996fada0dee.png"},{"id":58077700,"identity":"64eb5c4d-d6ed-4bae-a11d-c2e885f36990","added_by":"auto","created_at":"2024-06-10 22:40:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":25026,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of patients without dose reduction (blue) vs. with dose reduction (yellow) in relation to few (≥3) or more (≥4) TBs (n=130 patients in 485 MM-TBs)\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/994044a3163589d8c6da5d1c.png"},{"id":65104231,"identity":"ad9479f3-68a4-40bf-b5d0-e0a48d660aab","added_by":"auto","created_at":"2024-09-23 16:12:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1315017,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/8adb5038-6d37-41cf-9bba-97ec744ce8fc.pdf"},{"id":58077292,"identity":"1fdc5aa6-17be-4c51-9eea-deb37e272a4b","added_by":"auto","created_at":"2024-06-10 22:32:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":59822,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1.\u003c/strong\u003e Comparison of patients without dose reduction (blue) vs. with dose reduction (yellow) in 2 to ≥8 MM-TBs (n=130 patients in 485 MM-TBs)\u003c/p\u003e","description":"","filename":"2bSuppl.Fig.1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4432469/v1/fbaf75b810498d1881acba64.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Original Paper Optimizing individualized therapy decision-making in multiple myeloma (MM): Integration and impact of the Revised Myeloma Comorbidity Index in the MM-Tumor Board","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMultiple Myeloma (MM) is a hematological disease that predominantly affects elderly patients. The introduction of proteasome inhibitors (PI), immunomodulatory drugs (IMiDs) and immunotherapeutics (monoclonal and bispecific antibodies, antibody drug conjugates, chimeric antigen receptor (CAR)-T-cells), has significantly enlarged therapeutic options and has improved the prognosis, progression-free- (PFS) and overall survival (OS) of MM patients over the last 20 years.\u003csup\u003e1\u003c/sup\u003e Standard treatment for MM now involves triplet or quadruplet therapy which typically includes a combination of a PI, IMiDs, corticosteroid and monoclonal antibody.\u003csup\u003e2\u003c/sup\u003e Additionally, if patients are deemed fit enough, autologous stem cell transplantation (ASCT) followed by maintenance therapy is considered.\u003csup\u003e2\u0026ndash;6\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDue to the availability of numerous therapeutic options, treatment of MM has become more complex in recent years, allowing individualized treatment. It is known for example, that carefully selected older patients can benefit from intensive therapy as much as younger patients. These patients may also receive triplets or quadruplets, tolerate longer treatment sequences, and should be included in clinical trials.\u003csup\u003e2,7\u0026ndash;13\u003c/sup\u003e However, inclusion of elderly patients over the age of 70 years and of vulnerable individuals in clinical trials is notably infrequent. Consequently, determining the eligibility of individuals for intensive and/or novel treatment can be challenging.\u003csup\u003e7\u0026ndash;14\u003c/sup\u003e To identify suitable treatment options for these patients, functional assessment (FA) tools have been established.\u003csup\u003e7,8,10,13,14\u003c/sup\u003e A FA is a multidimensional, multidisciplinary approach to more objectively determine the functional health status of frail, vulnerable and/or elderly patients.\u003csup\u003e7\u0026ndash;14\u003c/sup\u003e Recently, MM-specific risk scores, such as the International Myeloma Working Group (IMWG)-frailty score, Revised-Myeloma Comorbidity Index (R-MCI), Mayo-risk score, and UK Myeloma Research Alliance Risk Profile, were compared using retrospective (test analysis) and prospective data (validation) to assess, whether they yield similar results. Moreover, FA is already utilized to guide therapeutic management.\u003csup\u003e10,13,14\u003c/sup\u003e However, in routine clinical practice, these tools are currently assessed and considered in only about 20% of myeloma patients, and the consistent integration of FA into MM-tumorboards (MM-TBs) for therapeutic decision-making has not been evaluated.\u003csup\u003e7\u0026ndash;14\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAt our Comprehensive Cancer Center Freiburg (CCCF), FA is conducted via the R-MCI. This validated MM-specific risk score can also be reliably conducted using retrospective data\u003csup\u003e14\u003c/sup\u003e and is consistently assessed in our MM patients before treatment initiation. Furthermore, it has been integrated into our electronic Tumorboard online system (TOS).\u003csup\u003e7\u0026ndash;10,13,14\u003c/sup\u003e The R-MCI web tool enables the immediate calculation of the R-MCI (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.myelomacomorbidityindex.org\" target=\"_blank\"\u003ewww.myelomacomorbidityindex.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.myelomacomorbidityindex.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003csup\u003e15\u003c/sup\u003e) for physicians, study nurses and research assistants.\u003c/p\u003e \u003cp\u003eAs FA, exemplified by the use of the R-MCI in MM-TB, and multidisciplinary care are novel standards in improving patient outcomes by finding the fine line between under- and overtreatment,\u003csup\u003e8,9,16\u003c/sup\u003e the aim of this study was to determine a) the extend and the reliability of the integration of the R-MCI in our MM-TB, b) its impact on treatment guidance at baseline and c) R-MCI changes during follow-up in consecutive MM patients at our center.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003ch2\u003e\u003cem\u003eData sources and study design\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWe performed this exploratory study in consecutive MM patients who were presented in our MM-TB at the CCCF, as described previously.\u003csup\u003e9,16\u003c/sup\u003e All patient information was recorded in the electronic documentation system, Medoc, and retrieved from it.\u003csup\u003e7,10,13,14,16\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePatient dispositions are outlined in Fig. 1: we retrieved 565 MM patients (100%) with 1256 MM-TB presentations (100%), being presented and discussed either once or repeatedly between February 2018 and June 2021. To maximize the use of prospective and unbiased data for the follow-up, we focused on patients with a minimum of two MM-TB presentations, anticipating at least two R-MCI assessments/patient (marked in light blue in Fig. 1: n=215 patients). This formed a cohort of 215 MM patients with multiple TB presentations (n=691), in which we evaluated the R-MCI data and number of MM-TB presentations/patient (2, 3, 4, 5, 6, 7, \u0026ge;8). Out of these 215 patients, 179 patients with 603 MM-TB presentations underwent prospectively performed R-MCI assessments and subsequent anti-myeloma-therapy. Follow-up R-MCI calculations were available for 130 of these patients (with 485 MM-TB presentations; marked in red in Fig. 1). This \u0026lsquo;follow-up cohort\u0026rsquo; was analyzed for patient characteristics which included age, MM staging, number of therapy lines at MM-TB assessment and therapy data (induction, maintenance or subsequent MM therapy).\u003c/p\u003e\n\u003cp\u003eThe aim of this study was to determine a) the extend and the reliability of the integration of the R-MCI in our MM-TB, b) its impact on treatment guidance at baseline [a) and b) performed in cohort of 215 MM patients with multiple TB presentations (n=691), marked in light blue in Fig. 1] and c) R-MCI changes during follow-up in consecutive MM patients at our center (n=130 patients, with 485 TB presentations, marked in red in Fig. 1). Moreover, we compared therapy intensity (dose reductions done vs. not) in subgroups of patients, categorized by frailty (R-MCI: fit, intermediate-fit, frail) vs. age (\u0026lt;60, 60-69, \u0026ge;70 years) in analogy to Holler et al.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed according to the guidelines of the Declaration of Helsinki and Good Clinical Practice. All patients gave their written informed consent for institutionally initiated research studies and analyses of clinical outcome studies conforming to the institutional review board guidelines. The ethics committee of the University of Freiburg (UKF) approved the trial protocol (EV, 81/10 + 22-1491-S1).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eR-MCI assessment\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe R-MCI comprises five weighted risk factors, namely renal and lung function, Karnofsky performance status (KPS), frailty and age. Additionally, it allows to include cytogenetics (CGs) if available.\u003csup\u003e7,8\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eSince the R-MCI had been integrated into our TOS at our UKF center to be readily available for patient- and fitness-related questions, we assessed its extent of coverage within the MM-TB.\u003c/p\u003e\n\u003cp\u003eIn cases, where the R-MCI had not been found integrated within the MM-TB (Fig. 3; 6%), we used the online R-MCI calculator (www.myelomacomorbidityindex.org\u003csup\u003e15\u003c/sup\u003e) to determine the R-MCI retrospectively, as descibed.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eDose reductions and follow-up analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eOur aim was to examine the impact of the R-MCI on therapy decisions, analogous to prior reports.\u003csup\u003e10,13\u003c/sup\u003e Therefore, we focused on patients who were initiated on anti-MM therapy after initial R-MCI assessment. We defined a shorter time span as compared to prior studies\u003csup\u003e10,13\u003c/sup\u003e, here of a maximum of 6 months between the R-MCI assessment and subsequent therapeutic decision to assess the possible impact of R-MCI changes within shorter time frames. Dose reduction was defined according to dose reduction recommendations in UKF/CCCF therapy handbooks and chemotherapy schedules\u003csup\u003e17,18\u003c/sup\u003e as described.\u003csup\u003e10\u003c/sup\u003e Decisions of dose reductions were based on physicians\u0026rsquo; choices,\u003csup\u003e10,13\u003c/sup\u003e but these were here influenced by TOS-integrated R-MCI data. This was different to previous data by Holler et al., where the R-MCI had not been obligatory to insert into our TOS-MM-TB.\u003csup\u003e10\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn 43 TB presentations (6%), the R-MCI had not been prospectively inserted into our TOS-MM-TB, thus was therein unassessed for the MM-TB discussion. In these cases, two physicians (ED+ME), both trained in onco-geriatrics, independently determined, whether chosen MM-decisions and given therapy suggestion would have been different, if the R-MCI had been assessed before therapy initiation (Fig. 4). Through these data, we could determine, whether therapy intensity aligned with the fitness levels determined via R-MCI, providing full dose for fit patients and reduced intensity for frail patients.\u003c/p\u003e\n\u003cp\u003eTo further assess the therapy decisions, we examined whether patients\u0026rsquo; constitution had changed in a follow-up analysis. Therefore, we evaluated the specific distribution of patients among R-MCI scores before start of therapy (T0) and follow-up (T1; Table 4). We also assessed the R-MCI changes over time, namely whether the R-MCI improved, remained unchanged or deteriorated (Fig. 5), in line with previous studies.\u003csup\u003e10,13\u003c/sup\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe trial was analyzed descriptively, providing means, median and range for continuous measures, and absolute and relative frequencies for categorical variables. The R-MCI was assessed and compared in age subgroups of \u0026lt;60-, 60-69- and \u0026ge;70-year-old patients, in analogy to prior analyses\u003csup\u003e10,13\u003c/sup\u003e (Tables 2+3), as well as at initial and subsequent (=follow-up) assessment (Table 4). Data were assessed using GraphPadPrism V5.03 and SAS 9.4 (SAS Institute Inc. USA) and were analyzed as of 1/2023.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cem\u003eNumber of MM-TB presentations per patient\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eFor patients with \u0026ge;2 MM-TB presentations (n=215, Fig. 1), we assessed the median TB-presentations/patient, which were three within our 3-year assessment period (2/2018 \u0026ndash; 6/2021), in line with prior analyses of our group (Fig. 2).\u003csup\u003e9,16,19\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eFig. 2 displays the number and frequencies of patients with repeated (2, 3, 4, 5, 6, 7 or \u0026ge;8) TB presentations. Within the 3-year study, most patients were presented within our MM-TB 2 or 3 times (71%), \u0026ge;4 presentations were found in 29% of patients and \u0026ge;6 presentations/patient were rare (9%, Fig. 2).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eR-MCI adherence at the MM-TB and prospectively vs. retrospectively assessed R-MCI\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWithin 691 MM-TBs (Fig. 1+2), prospective R-MCI scores were available in 94% (648/691 MM-TB protocols, Fig. 3). In the remaining 6% of presentations (n=43), the R-MCI was calculated retrospectively.\u003c/p\u003e\n\u003cp\u003eRegarding the R-MCI subgroups of the prospectively assessed scores, 30% patients were classified as fit (R-MCI 0-3), 52% as intermediate-fit (R-MCI 5-6) and 18% as frail (R-MCI 7-9) in line with prior analyses (Fig. 3, left column).\u003csup\u003e7,9,10,13,16\u003c/sup\u003e In the few retrospectively scored presentations, fit, intermediate and frail patients were observed in 16%, 58% and 26%, respectively (Fig. 3, right column). Thus, patients with non-included R-MCI assessment within the MM-TB TOS seemed 1.9-fold less fit (30%\u0026rarr;16%) and 1.1-fold more intermediate-fit (52%%\u0026rarr;58%) or 1.4-fold frailer (18%\u0026rarr;26%) as compared to the prospectively evaluated cohort (Fig. 3).\u003c/p\u003e\n\u003ch2\u003eDifferences in therapy decisions without prospective R-MCI assessment\u003c/h2\u003e\n\u003cp\u003eIn 43 MM-TB presentations (6%), the R-MCI had not been utilized to aid the TB decision (Fig. 3). In 40 cases (93%), the MM-TB decisions (reassessed by ED+ME) were not found to have been chosen differently (Fig. 4). However, in three patients, both physicians (ED+ME) would have modified treatment according to the R-MCI. Notably, all three were frail according to the R-MCI, including the only \u0026lt;60-year-old patient with an R-MCI of 7/9.\u003c/p\u003e\n\u003cp\u003eThe first 78-year-old male patient had received dose-reduced bortezomib-cyclophosphamide-dexamethasone (VCd), although, due to his R-MCI of 9/9 (=utmost frailty), Vd might have been more appropriate retrospectively. The second 79-year-old female patient with an R-MCI of 8/9 had received rituximab-bortezomib-dexamethasone treatment due to high CD20 plasma cell expression, where best supportive care (BSC) would have been more appropriate retrospectively. The third 53-year old male patient with an R-MCI of 7/9 had received Daratumumab-Vd (DVd, adapted according to the Alcyone study\u003csup\u003e20\u003c/sup\u003e) and was initially intended to undergo ASCT due to his age. Retrospectively, the therapeutic choice would have been DVd alone. Thus, the outcome (progressive disease in 3/3, subsequent hospitalization in 3/3 and substantial dose reduction being necessary in 2/3 and BSC in 1/3) of all three frail patients suggested that better therapy choices could have been made, if the R-MCI had been utilized to aid in the therapeutic process. Notably, MM-related death occurred in 2/3 patients.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003ePatient characteristics\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWe focused on 130 patients with \u0026ge;2 MM-TB presentations/patient (with 485 MM-TB presentations), subsequent anti-MM treatment and R-MCI follow-up assessment (Fig. 1 + Table 1). Their median age of 66 years (range 38-86) at initial presentation was typical for referral and university centers, with 62% being male and 38% female. Expectedly, the most common paraprotein types were IgG and kappa light-chains in 56% and 71%, respectively (Table 1). Advanced ISS stage (2 or 3) was frequent with 68%. During the observation period, a median of two therapy lines/patient (range 1-9) had been performed, with induction, maintenance, and later-line (relapse) therapy being performed in 31%, 17% and 52%, respectively.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAge subgroups and further analysis of the distribution of R-MCI scores within their groups\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eAge subgroups of patients \u0026lt;60, 60-69 and \u0026ge;70 years were equally distributed with 34%, 30% and 36%, respectively (Table 2). Expectedly, younger patients aged \u0026lt;60-years were mostly fit (64%) or intermediate-fit (34%), while frail patients were rare (2%). In the group of 60-69-year-old patients, a substantial shift from fewer fit (33%) to more intermediate-fit (54%) and frail patients (13%) was noted. Even more strikingly, however, 9% of \u0026ge;70-years-old patients were classified as fit, whereas most (55%) were intermediate-fit, and 36% were frail (Table 2). Thus, being fit was 4.5-times more prevalent in elderly patients than frailty in young patients.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003ePatient- and therapy-relevant differences in entire cohort and R-MCI and age subgroups\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eDifferences in patient frequencies, median age and dose reduction in the entire patient group, as well as in R-MCI vs. age subgroups are summarized in Table 3. While dose reduction in the entire patient group occurred frequently (55%), this was less common in R-MCI fit patients (38%), and increased in intermediate-fit and frail patients to 61% and 74%, respectively.\u003c/p\u003e\n\u003cp\u003eNotably, dose reduction in \u0026lt;60-, 60-69- and \u0026ge;70-year-old patients were performed in 45%, 49% and 70%, respectively. Thus, dose reduction was less common in fit patients than in \u0026lt;60-year-old patients. Conversely, in intermediate-fit and frail patients, dose reduction occurred more frequently than in 60-69- and \u0026ge;70-year-old patients (Table 3).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eR-MCI changes before start of therapy (T0) vs. follow-up (T1; serial R-MCI assessment)\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eSerial R-MCI assessments were available for 130 patients within 485 MM-TB presentations and with anti-MM therapy being performed (Fig. 1). Our follow-up assessment of potential R-MCI changes was here conducted earlier than in previous analyses (after a median of 5 rather than previously after 11 months).\u003csup\u003e10,13\u003c/sup\u003e The mean and median R-MCI at T0 were 4.3 and 4 (intermediate-fit) and at T1 4.7 and 5 (remaining intermediate-fit), respectively (Table 4). The precise distribution of patients among R-MCI scores at T0 and T1 is displayed in Table 4. Notably, over the median follow-up period of 5 months (range: 0-25), the number of fit patients slightly decreased (T0: 34.6% \u0026rarr; T1: 27%), while the number of intermediate-fit patients increased (T0: 47.7% \u0026rarr; T1: 56%), and the number of frail patients remained stable (T0: 17.7% \u0026rarr; T1: 17%).\u003c/p\u003e\n\u003cp\u003eAdditionally, we assessed in all patients, whether their constitution via R-MCI changed within our follow-up period: in 55%, this improved or remained unchanged, whereas in 45%, a decline was noted (Fig. 5).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eDose reduction in relation to number of MM-TB presentations\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eIn terms of dose reduction, we also analyzed, whether frequencies of dose reduction were related to the number of TB presentations/patient, namely, whether with lesser vs. more frequent TB discussions, dose-reductions increased due to MM patients\u0026rsquo; quality of life (QoL) decreasing with subsequent treatment lines, as described previously (Fig. 6).\u003csup\u003e21\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn patients with 2 or 3 TB-presentations, no dose reduction vs. dose reduction were performed in similar frequencies with 51% and 49%, respectively. This was different in patients with more advanced or difficult-to-treat MM showing \u0026ge;4 TB-presentations: no dose reduction was here performed in only 36%, whereas dose reduction was much more frequent in 64% (Fig. 6). The frequencies of no dose reduction vs. dose reduction in each subsequent 2 to \u0026ge;8 TB frequencies are outlined in Suppl. Fig. 1.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSince therapy decision-making is ideally supported by FA to individualize treatment especially for frail patients, we integrated the R-MCI into our MM-TB.\u003csup\u003e9\u003c/sup\u003e This integration allows all users to readily distinguish fit from frail patients and expeditiously adjust therapy intensity during our weekly performed interdisciplinary MM-TB discussion.\u003csup\u003e9,10,13,14\u003c/sup\u003e While various functional tests, including different comorbidity scores and geriatric functional tests have been examined,\u003csup\u003e13,27\u0026ndash;30\u003c/sup\u003e the R-MCI was explicitly helpful to individualize treatment decisions and improving the tolerance of MM therapy.\u003csup\u003e10\u003c/sup\u003e Additionally, the R-MCI has been recognized as the only comorbidity index that did not show significant differences in risk group distribution for both retrospective and prospective data, thus it was reliably assessable from both data sets.\u003csup\u003e14\u003c/sup\u003e Another convenience is the user-friendly R-MCI homepage (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.myelomacomorbidityindex.org\" target=\"_blank\"\u003ewww.myelomacomorbidityindex.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.myelomacomorbidityindex.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003csup\u003e15\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eWhile fitness assessments are used for tailoring therapy in other hematological diseases, these are not routinely established in MM patients, despite studies aiming to elucidate their usefulness.\u003csup\u003e10,13,31\u003c/sup\u003e FA have been described as challenging to integrate into everyday clinics due to time constraints.\u003csup\u003e13,32\u0026ndash;34\u003c/sup\u003e The pivotal outcome of our study was the successful integration of the R-MCI into MM-TB protocols in \u0026gt;\u0026thinsp;90%, confirming previous studies of the R-MCI being resourceful.\u003csup\u003e7\u0026ndash;10,13,14,24,33\u003c/sup\u003e The establishment of the R-MCI in our MM-TB exemplified that frailty scores can be readily used in everyday clinics. Albeit the R-MCI calculation is specifically requested in our TOS MM-TB system, its use and integration for each patient therein was not obligatory within TOS during the assessment period, therefore the availability in \u0026gt;\u0026thinsp;90% of our large MM-TB cohort (n\u0026thinsp;=\u0026thinsp;691 MM-TB cases; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was a success. Of note, the R-MCI was unavailable in 43 patients (6%) only, who had been externally referred to our UKF/CCCF: either missing data were reasons for its non-use, or physicians from different disciplines/departments were overriding the TOS-integrated R-MCI scoring. In these patients, the subjective assessment of the introducing physicians within the MM-TB sessions was utilized (which would have otherwise been complemented by the R-MCI). Meanwhile, we have improved the TOS MM-TB software to make it mandatory to enter the R-MCI parameters required for its calculation and thereby ensuring that R-MCI scores are available in 100% of patients. Consistent with previous analyses, we affirmed the rarity (2%) of frailty in \u0026lt;\u0026thinsp;60-year-old patients but acknowledged its significance. This was indeed important to determine, because in the only frail 53-year-old patient, CD38-based induction and ASCT had been the TB-recommendation, whereas CD38-based therapy alone would have been the better TB-choice according to the R-MCI assessment. We observed an increase in frailty to 36% in \u0026ge;\u0026thinsp;70-year-old patients, albeit among them also 9% were fit and 55% were intermediate-fit. Dose reduction was performed in alignment with fitness levels in 38% in fit, 61% in intermediate-fit and 74% in frail patients. Decision-making without an available R-MCI revealed that in three frail patients, therapeutic decision could have been facilitated with exact knowledge of patients\u0026rsquo; fitness. Consequently, therapy choices would have differed, if the R-MCI had been assessed before therapy initiation.\u003c/p\u003e \u003cp\u003eOf note in this study and different to others\u003csup\u003e10,13\u003c/sup\u003e was, that our follow-up assessment of potential R-MCI changes was conducted earlier, after a median of 5 months, and that the R-MCI showed fitness improvement or stability in 55%, while a decline was observed in 45% of cases. In previous studies, where the follow-up was conducted after a median of 11 months, the R-MCI showed rather an improvement in 90% of patients than decline in only 10%.\u003csup\u003e10,13\u003c/sup\u003e This indicates that it may be more advisable to evaluate changes in fitness and quality of life (QoL) after a longer period following the initiation of therapy, in order to prevent temporary therapy side effects from affecting QoL.\u003csup\u003e10,13,21,35\u003c/sup\u003e Therefore, to possibly better capture MM patients\u0026rsquo; advances in performance, therapy endurance and QoL, a defined latency of approximately 1 year appears more suitable than \u0026lt;\u0026thinsp;6 months. Likewise, the common practice of repeatedly assessing QoL domains (i.e. in QoL questionnaires in clinical studies) over very short periods may be less practical in view of our data.\u003csup\u003e10,13,21,35\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur assessment of the MM-TB over a 3-year period revealed that 38% of patients were presented at least twice, resulting in at total of 691 MM-TB presentations. Among these patients, 71% had 2\u0026ndash;3 MM-TB presentations within our observation period, while 29% had\u0026thinsp;\u0026ge;\u0026thinsp;4 presentations, and 9% had\u0026thinsp;\u0026ge;\u0026thinsp;6, supporting our view on very frequent TBs.\u003csup\u003e19\u003c/sup\u003e MM-TB outcome data of 2020/21\u0026thinsp;\u0026minus;\u0026thinsp;\u003csup\u003e9\u003c/sup\u003e and 2012-2014-analyses\u003csup\u003e16\u003c/sup\u003e as well as our data here seem valuable, as we had previously described the postulated survival benefit in patients with \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;3 TB discussions as error-prone, occurring due to an immortal time bias (since patients need to survive long enough to be discussed more often). Therefore, time-biased results should not lead to the conclusion that more TBs will increase patients' survival. Instead, insightful discussions within one or few meaningful, long-lasting TBs, ideally in interdisciplinary teams, will generate most profound results for cancer patients.\u003csup\u003e19,36\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOf interest was, that the number of dose-reduced therapies in our entire cohort was higher than in previous studies (55% vs 41%\u003csup\u003e10\u003c/sup\u003e, respectively). This difference was likely related to our focus on MM-TB-patients, whereas Holler et al. had assessed physician-based therapeutic decisions of consecutive MM patients.\u003csup\u003e10\u003c/sup\u003e Our results revealed that dose adaptions were regularly performed in frail patients. Although age-based dose reduction was also observed, they seemed more error-prone than if the R-MCI was included in the decision-making: older patients (\u0026ge;\u0026thinsp;70 years) were treated with dose reduction in 70%, albeit only 36% of them were frail, while 9% were fit and 55% were intermediate-fit. Consequently, this group of patients was rather undertreated in substantial numbers, as previously described.\u003csup\u003e8\u003c/sup\u003e In line, younger patients can be frail and are important to decipher likewise. Therefore, the assumption that younger patients should always receive full-dose treatment, and elderly patients should not, may often be error-prone. This confirms that age alone is not sufficient to determine patients\u0026rsquo; health status and therapy endurance. Instead, FA is superior in specifying patients\u0026rsquo; constitution and biological age\u003csup\u003e7\u0026ndash;14,24\u003c/sup\u003e which is why treatment decisions should rather depend on FA tools, such as R-MCI or others.\u003csup\u003e12,23,24,27\u0026ndash;30\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStrengths of our analysis included the precise examination of a large MM-TB cohort, the repeated R-MCI analysis, and the observed dose reduction, well-associated with R-MCI-, rather than age-subgroups. Our observation period of 3 years was substantial, and the detailed examination of patients with various numbers of TB presentations and deterioration in their health status (R-MCI) exhibited their complexity. This is in line with a prior analysis in MM patients with first- vs. later lines of therapy as compared to BSC,\u003csup\u003e21\u003c/sup\u003e which, however, did not assess QoL changes - as here - in consecutive but different follow-up cohorts. Our analysis was well comparable to prior analyses\u003csup\u003e9,16,19\u003c/sup\u003e and revealed the quality of one out of 24 TBs at our UKF/CCCF: while the quality results of our MM-TB, the decisions, pathway- and guideline-adherence, TB-compliance, referrer satisfaction, and improvement of clinical trial inclusion have been described previously,\u003csup\u003e9,16,19\u003c/sup\u003e our data here proved that FA integrated into TBs is feasible and does support therapy decisions.\u003c/p\u003e \u003cp\u003eLimitations of the study were the single-institution approach and the range of patients\u0026rsquo; ages (38\u0026ndash;86 years), with 64% of patients being \u0026lt;\u0026thinsp;70 years old. This is, however, typical for MM patients in tertiary centers and suggests that our data are even more relevant in older patients. Additionally, the specific conditions for our study inclusion (MM-TB presentations\u0026thinsp;\u0026ge;\u0026thinsp;2, subsequent therapy being instituted, and performed follow-up R-MCI) focused on more complex MM patients (and a subset of our initial study cohort, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Our cohort did include patients receiving different treatment with induction, maintenance and later-line treatment, since our aim was not survival analyses, rather than to assess the completeness of the R-MCI within our MM-TB, whether therapy decisions in terms of fitness vs. age cohorts were different and how dose-reductions were performed. The aim of this study was therefore not to determine exact therapy choices of newly diagnosed MM vs. relapsed/refractory MM, or within different therapy lines, nor whether patients did profit from dose-reductions, because we and others had shown this in prior publications.\u003csup\u003e7,8,10,27\u0026ndash;30,37\u0026ndash;44\u003c/sup\u003e Moreover, our follow-up assessment was conducted within a relatively short period which should ideally be performed after ~\u0026thinsp;1 year, according to Scheubeck and Holler.\u003csup\u003e10,13\u003c/sup\u003e Another criticism may arise from the retrospective evaluation of three patients (whose R-MCI was unavailable in TOS and who received different, more intensive treatment due to the unavailability of their R-MCI). This introduced bias as their outcome was known during our reassessment of therapy choices. Last, since we had examined survival repeatedly in similar MM cohorts, via R-MCI and age subgroups and in different MM-TB cohorts,\u003csup\u003e7\u0026ndash;10,13,14,16\u003c/sup\u003e this was not repeated here.\u003c/p\u003e \u003cp\u003eIn conclusion, our results demonstrate the widespread use of the R-MCI within the MM-TB. Further research through prospective clinical trials seems essential to determine optimal, personalized treatment options for each patient. Building on this approach, Mian et al. published a systematic review including 43 clinical trials considering frailty tools and showed an encouraging trend to incorporate frailty assessments in clinical evaluations and treatment decisions,\u003csup\u003e41\u003c/sup\u003e in line with our data of the R-MCI-integration in TOS-MM-TBs in \u0026gt;\u0026thinsp;90%. The association between the R-MCI and chosen therapy intensity was better than via age cohorts, which further underlines that the R-MCI is a more precise predictor than age alone. We could show that the recommendations to establish therapy decisions on FA can be directly implemented in TBs. Therapy decisions for intermediate-fit patients appear more complex than for fit and frail patients, because some intermediate-fit patients may endure full-dose treatment, while others need dose-reduction. Therefore, this group of patients should be analyzed further. Today, some MM experts distinguish only two groups of fit vs. frail patients.\u003csup\u003e6,10,38\u003c/sup\u003e Prospective studies using the R-MCI as an important tool for therapeutic decision-making are in process at our CCCF. Most importantly, these and other important TB analyses have led to our better interpretation of cancer care, in close collaboration with statisticians\u003csup\u003e16,22,45\u0026ndash;47\u003c/sup\u003e, which is essential to produce reliable evidence for future progress. We are grateful that these productive collaborations continue to exist at our and other CCCs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: The authors thank DSMM, GMMG, EMN and IMWG experts for their support and prior recommendations on this study. We thank all MM patients who participated in this study and the entire MM-TB, especially Drs. Henning Sch\u0026auml;fer (radiation oncology), PD Jakob Neubauer (radiation department), Marc-Antoine Calba (pathology), Daniel Textor, Jan Barleben and Cornelius Struck (CCCF Tumorboard Online System (TOS)), Mandy-Deborah M\u0026ouml;ller (sport support group), Johannes Jung (TUR M\u0026uuml;nchen), Johannes Waldschmidt (W\u0026uuml;rzburg), Cornelius Miething, and Michael Rassner (all others UKF), for their inspirations, dedication and thrive to achieve best results for our MM patients. The results were presented in part at the \u0026apos;German, Austrian and Swiss annual Hematology \u0026amp; Oncology meetings\u0026apos; (DGHO), MM workshop meetings in Freiburg and Saig Med1 retreat meetings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Ethics: \u003c/strong\u003e(EV EK 22-1491-S1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability: \u003c/strong\u003eThe data that support the findings of this study are available from the corresponding author (ME) upon reasonable request\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e: All authors have no conflicts of interest regarding the content. \u003cbr\u003e \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources: \u003c/strong\u003eNo funders to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: ME, RW and GI designed the research, ED, ME, and GI performed the analysis, analyzed the results and prepared tables and figures. ED and ME wrote the original draft of the paper. RW, GI, JR, HR, MH, GH and CG critically reviewed and edited the paper. All authors approved the final version of the paper.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStadtmauer EA (2024) Antibody-Based Therapy for Transplantation-Eligible Patients with Multiple Myeloma. N Engl J Med 390(4):368\u0026ndash;369\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSonneveld P, Dimopoulos MA, Boccadoro M et al (2024) Daratumumab, Bortezomib, Lenalidomide, and Dexamethasone for Multiple Myeloma. N Engl J Med 390(4):301\u0026ndash;313\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVoorhees PM, Sborov DW, Laubach J et al (2023) Addition of daratumumab to lenalidomide, bortezomib, and dexamethasone for transplantation-eligible patients with newly diagnosed multiple myeloma (GRIFFIN): final analysis of an open-label, randomised, phase 2 trial. 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Am Soc Clin Oncol Educ Book Am Soc Clin Oncol Annu Meet 39:500\u0026ndash;518\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoulson AB, Royle K-L, Pawlyn C et al (2022) Frailty-adjusted therapy in Transplant Non-Eligible patients with newly diagnosed Multiple Myeloma (FiTNEss (UK-MRA Myeloma XIV Trial)): a study protocol for a randomised phase III trial. BMJ Open 12(6):e056147\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson JR, Cain KC, Gelber RD (2008) Analysis of survival by tumor response and other comparisons of time-to-event by outcome variables. J Clin Oncol Off J Am Soc Clin Oncol 26(24):3913\u0026ndash;3915\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIhorst G, Waldschmidt J, Schumacher M, W\u0026auml;sch R, Engelhardt M (2015) Analysis of survival by tumor response: have we learnt any better? Ann Hematol 94(9):1615\u0026ndash;1616\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDold SM, M\u0026ouml;ller M-D, Ihorst G et al (2021) Validation of the revised myeloma comorbidity index and other comorbidity scores in a multicenter German study group multiple myeloma trial. Haematologica 106(3):875\u0026ndash;880\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Characteristics of actively treated MM patients with follow-up R-MCI assessment (n=130)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian (range)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at therapy initiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e66 (38-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMales : females\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e81 (62) : 49 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMM type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; IgG / IgA / IgM / biclonal / LC only\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Kappa / lambda / biclonal\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; AL-Amyloidosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73 (56) / 20 (15) / 2 (2) / 2 (2) / 33 (25)\u003c/p\u003e\n \u003cp\u003e92 (71) / 36 (28) / 2 (1)\u003c/p\u003e\n \u003cp\u003e3 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eISS stage\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; I / II / III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e39 (32) / 37 (30) / 47 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTherapy lines @ MM-TB assessment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e2 (1-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.25200642054575%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInduction (first-line) MM therapy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eUnder maintenance therapy Subsequent (later line) MM therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"39.96789727126806%\"\u003e\n \u003cp\u003e40 (31)\u003c/p\u003e\n \u003cp\u003e22 (17)\u003c/p\u003e\n \u003cp\u003e68 (52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.780096308186195%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: MM: multiple myeloma; ISS: international staging system; @: at\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Distribution of age subgroups and within their group the number and proportion fit, intermediate-fit and frail patients via R-MCI (n=130)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.03205128205128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.03205128205128%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.93589743589744%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eR-MCI subgroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge subgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEntire group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntermediate-fit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrail\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026lt;60 years (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e44 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e28 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e15 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e1 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; 60-69 years (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e39 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e13 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e21 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e5 (13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e \u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e70 years (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e47 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e4 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e26 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e17 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Patient- and therapy-relevant differences in entire and R-MCI- vs. age subgroups in frequencies, age and treatment performed without (w/o) vs. with (w) dose reduction\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"705\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.772727272727273%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.352272727272727%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEntire group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.50568181818182%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eR-MCI subgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.36931818181818%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge subgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.793741109530583%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFit\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntermediate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.806543385490754%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrail\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;60 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.944523470839261%\"\u003e\n \u003cp\u003e\u003cstrong\u003e60-69 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;\u003c/strong\u003e\u003cstrong\u003e70 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.793741109530583%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e130 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e45 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e62 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.806543385490754%\"\u003e\n \u003cp\u003e23 (18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e44 (34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.944523470839261%\"\u003e\n \u003cp\u003e39 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e47 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.793741109530583%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian age (range)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e66 (38-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e58 (38-78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e68 (48-84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.806543385490754%\"\u003e\n \u003cp\u003e77 (72-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e55 (38-59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.944523470839261%\"\u003e\n \u003cp\u003e65 (60-69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e77 (70-86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.793741109530583%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients w/o dose reduction (%) / w dose reduction (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e58 (45) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e72 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e28 (62) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.37126600284495%\"\u003e\n \u003cp\u003e24 (39) /\u003c/p\u003e\n \u003cp\u003e36 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.806543385490754%\"\u003e\n \u003cp\u003e6 (26) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17 (74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e24 (55) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20 (45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.944523470839261%\"\u003e\n \u003cp\u003e20 (51) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e19 (49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.2375533428165%\"\u003e\n \u003cp\u003e14 (30) /\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: intermediate: intermediate-fit, w/o: without, w: with\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;Comparison of R-MCI at T0 versus T1 with number of patients and Mean / Median (range) values\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"661\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u003cstrong\u003eR-MCI subgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e\u003cstrong\u003eR-MCI 0-9 (n=130)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT0 = initial assessment\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(# of patients)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e\u003cstrong\u003eT1 = follow-up assessment\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(# of patients)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003eFit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e19 \u0026nbsp; \u0026nbsp;(0-3: n=45=34.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e21 \u0026nbsp; \u0026nbsp;(0-3: n=35=27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003eIntermediate-fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e12 \u0026nbsp; \u0026nbsp;(4-6: n=62=47.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e19 \u0026nbsp; \u0026nbsp;(4-6: n=73=56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003eFrail\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e0 \u0026nbsp; \u0026nbsp; \u0026nbsp;(7-9: n=23=17.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e1 \u0026nbsp; \u0026nbsp; \u0026nbsp;(7-9: n=22=17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.486404833836858%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.41389728096677%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMean / Median (range)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e4.3 / 4 (0-8)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.54984894259819%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e4.7 / 5 (0-9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: T0: initial R-MCI assessment before treatment initiation, T1: follow-up assessment of potential R-MCI changes after treatment and median follow-up of 5 months\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Multiple Myeloma (MM), tumor boards (TBs), Revised Myeloma Comorbidity Index (R-MCI), therapy adjustment, geriatric assessment, frailty","lastPublishedDoi":"10.21203/rs.3.rs-4432469/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4432469/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eIntroduction\u003c/b\u003e: Multiple Myeloma (MM) is a hematological disease predominantly affecting elderly patients. The complexity of current treatment necessitates individualized approaches. Therein, functional assessment (FA) tools, such as the Revised Comorbidity Index (R-MCI) at our University- and Comprehensive Cancer Center Freiburg, play a crucial role. This study aimed to determine a) the implementation of the R-MCI in our MM-tumor board (MM-TB), b) its impact on treatment guidance at baseline and c) potential changes during follow-up.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e: This exploratory study investigated R-MCI coverage and distribution in a cohort of patients with multiple TB presentations. Among them, a follow-up patient cohort undergoing subsequent MM-therapy was analyzed to determine treatment adjustments and changes in patients\u0026rsquo; condition measured by R-MCI alterations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e: During our 3-year assessment period, 565 patients were presented in our MM-TB, totaling 1256 TB-presentations. In the multiple TB presentation cohort, the median number of TB presentations was 3 (range: 2\u0026ndash;12). R-MCI scores within the MM-TB were available in 94%, whereas in 6%, the R-MCI had not been integrated. Among these, potential failure to identify the need for treatment modifications was determined. In the follow-up cohort, patient characteristics were typical for referral/university centers. Dose reductions were performed in 55% and were more prevalent among patients with \u0026ge;\u0026thinsp;4 vs. lesser TB presentations. Most patients (55%) showed a fitness stabilization or improvement via follow-up R-MCI.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e: R-MCI integration in MM-TB exceeded\u0026thinsp;\u0026gt;\u0026thinsp;90%, indicating its successful integration for treatment support. Our results underscore its value in guiding therapy decisions, providing a comprehensive assessment beyond age considerations.\u003c/p\u003e","manuscriptTitle":"Original Paper Optimizing individualized therapy decision-making in multiple myeloma (MM): Integration and impact of the Revised Myeloma Comorbidity Index in the MM-Tumor Board","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-10 22:32:23","doi":"10.21203/rs.3.rs-4432469/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-23T13:13:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-23T12:26:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293984623719007938567542739171599402335","date":"2024-08-23T12:15:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321676381571231703300756756371689414145","date":"2024-08-20T08:03:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-22T15:56:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"239559500893086270058433772786877654126","date":"2024-07-09T07:56:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61523312357692854121417826567871164975","date":"2024-06-29T15:40:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-27T07:30:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-24T14:27:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-24T14:27:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Hematology","date":"2024-05-16T16:55:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"901e2f0f-b62b-4c4f-9b2a-b8afe0be9abd","owner":[],"postedDate":"June 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T16:07:57+00:00","versionOfRecord":{"articleIdentity":"rs-4432469","link":"https://doi.org/10.1007/s00277-024-06010-5","journal":{"identity":"annals-of-hematology","isVorOnly":false,"title":"Annals of Hematology"},"publishedOn":"2024-09-21 15:57:34","publishedOnDateReadable":"September 21st, 2024"},"versionCreatedAt":"2024-06-10 22:32:23","video":"","vorDoi":"10.1007/s00277-024-06010-5","vorDoiUrl":"https://doi.org/10.1007/s00277-024-06010-5","workflowStages":[]},"version":"v1","identity":"rs-4432469","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4432469","identity":"rs-4432469","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}