Evidence map›Paper›PMID 42425530›Full record

ReviewEuropean journal of haematology2026

Bridging Randomized Trial Efficacy and Real-World Effectiveness in Multiple Myeloma: Integrating Clinical Trials and Real-World Evidence for Individualized Care.

Enrica Antonia Martino, Ernesto Vigna, Antonella Bruzzese, Nicola Amodio, Santino Caserta, Eugenio Lucia, Graziella D'Arrigo, Virginia Olivito, Caterina Labanca, Francesco Mendicino and 4 more

Abstract readReview
In one paragraph

Review in European journal of haematology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Enrica Antonia MartinoDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Ernesto VignaDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Antonella BruzzeseDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Nicola AmodioDepartment of Experimental and Clinical Medicine, University of Catanzaro, Catanzaro, Italy.
Santino CasertaDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Eugenio LuciaDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Graziella D'ArrigoIstituto di Fisiologia Clinica del CNR di Reggio Calabria, Consiglio Nazionale Delle Ricerche, Reggio Calabria, Italy.
Virginia OlivitoDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Caterina LabancaDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Francesco MendicinoDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.ORCID https://orcid.org/0000-0001-6339-632X
Maria Eugenia AlvaroDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.
Giovanni TripepiIstituto di Fisiologia Clinica del CNR di Reggio Calabria, Consiglio Nazionale Delle Ricerche, Reggio Calabria, Italy.
Fortunato MorabitoDane Srl, Reggio Calabria, Italy.
Massimo GentileDepartment of Onco-Hematology, AO of Cosenza, Cosenza, Italy.ORCID https://orcid.org/0000-0002-5256-0726

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM) is predominantly a disease of older adults, yet the randomized clinical trials (RCTs) that define standards of care are conducted largely in younger, fitter, and less comorbid populations. This creates a systematic mismatch between the populations generating evidence and those receiving treatment in routine practice, which can be characterized by comparing eligibility criteria, baseline characteristics, treatment exposure, and outcomes across RCTs and large real-world cohorts. Real-world data (RWD) have emerged as an essential complement to RCTs, capturing treatment effectiveness, tolerability, and patterns of care in unselected populations. Still, their use in clinical decision-making remains inconsistent. In this review, we use MM as a model to examine the divergence between trial efficacy and real-world effectiveness. Outcomes observed in RCTs are reproducible primarily in patients who resemble trial populations. In contrast, in older, frail, and comorbid patients, effectiveness is frequently attenuated by increased toxicity, reduced dose intensity, and early treatment discontinuation. We summarize how differences in comorbidity burden, frailty status, treatment intensity, and early discontinuation contribute to attenuated outcomes in routine care. Frailty, rather than chronological age alone, appears to be the principal determinant of this divergence. Despite its strong prognostic and predictive value, frailty is inconsistently measured in both RCTs and RWD, limiting the translation of evidence into practice. We highlight the prognostic and predictive value of formal frailty assessment and its current under-use in both RCTs and RWD. On this basis, we propose a pragmatic, patient-centered approach that uses trial-derived estimates of regimen efficacy together with real-world data on toxicity, dose intensity, and treatment persistence to enable systematic adaptation of regimen choice, dose, and schedule. Finally, we outline methodological priorities for future research, including standardized data elements, robust causal-inference approaches, routine incorporation of frailty, and closer alignment between RCTs and RWD. Although focused on MM, this framework has broader implications across hematologic malignancies, where bridging the gap between efficacy and effectiveness is essential to ensure that therapeutic advances translate into meaningful benefit for patients seen in everyday clinical practice.

Indexed as

Multiple MyelomaPrecision MedicineHumansPrognosisRandomized Controlled Trials as TopicTreatment Outcome

Identifiers

PMID42425530
PMCPMC13643620

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.