ReviewHematology. American Society of Hematology. Education Program2022
Fitness and frailty in myeloma.
Review in Hematology. American Society of Hematology. Education Program, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Machine learning risk stratification strategy for multiple myeloma: Insights from the EMN-HARMONY Alliance platform.HemaSphere · 2025Article
- How First-Line Therapy is Changing in non-Transplant Eligible Multiple Myeloma Patients.Mediterranean journal of hematology and infectious diseases · 2025Review
- What is the ideal approach-doublet, triplet, or quadruplet(s)?Hematology. American Society of Hematology. Education Program · 2024Review
- Racial disparities in multiple myeloma and access to stem cell transplantation.Blood cancer journal · 2024Article
- Article
- Perspectives on the Treatment of Multiple Myeloma.The oncologist · 2024Review
- Difficult-to-treat patients with relapsed/refractory multiple myeloma: A review of clinical trial results.EJHaem · 2023Review
- Management of Multiple Myeloma: A Review for General Practitioners in Oncology.Current oncology (Toronto, Ont.) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
As the aging population grows, so too does the number of well-tolerated antimyeloma therapies. Physicians will see an increasing volume of patients for subsequent lines of therapy, which could now extend this relationship for over a decade. For younger patients, treatment choices are infrequently impacted by concerns of fitness, but instead about effecting the deepest, most durable response. Older adults, in contrast, are more likely to experience under- than overtreatment, and therefore more objective (and ideally straightforward) ways to evaluate their fitness and ability to tolerate therapy will increasingly assist in decision-making. Post hoc analyses categorizing the fitness of trial patients in the modern treatment era globally demonstrate that even in highly selected populations, those that are recategorized as less fit or frail are consistently at higher risk of inferior outcomes and increased toxicities. Real-world data are comparatively lacking but do demonstrate that most patients with myeloma are not representative of those enrolled on clinical trials, generally more heavily burdened by comorbidities and more likely to be categorized as "less than fit." Simultaneously, the number of therapeutic options open to patients in the relapsed setting continues to grow, now including T-cell engagers and cellular therapies, with their unique toxicity profiles. The aim of this review is to summarize the available data, highlight some of the approaches possible to easily assess fitness and how results might inform treatment selection, and illustrate ways that patients' condition can be optimized rather than lead to exclusion from the more complex therapies newly available.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.