Evidence map›Paper›PMID 36989073›Full record

ArticleCancer2023

A real-world data analysis of predictors of early mortality after a diagnosis of multiple myeloma.

Shakira J Grant, Tanya M Wildes, Ashley E Rosko, Juliet Silberstein, Smith Giri

Open access · bronzeAbstract read
In one paragraph

Article in Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

13 citing papers in PubMed, 11 citations in OpenAlex.

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  13. Partnering With All Patients: Ensuring Shared Decision Making and Evidence-Based Management for Underrepresented Groups With Multiple Myeloma.American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting · 2023
    Article
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

5 authors at 4 institutions in 1 country.

Shakira J GrantDivision of Hematology, Department of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-8481-3046
Tanya M WildesDivision of Hematology/Oncology, University of Nebraska Medical Center/Nebraska Medicine, Omaha, Nebraska, USA.
Ashley E RoskoDivision of Hematology, Department of Medicine, The Ohio State University, Columbus, Ohio, USA.ORCID 0000-0001-5875-3214
Juliet SilbersteinSchool of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Smith GiriInstitute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, Alabama, USA.ORCID 0000-0002-1827-5032
University of North Carolina at Chapel Hill · USNebraska Medical Center · USThe Ohio State University · USUniversity of Alabama at Birmingham · US

Funding

UNC Oncology K12K12CA120780 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI WILLIAM Y. KIM · 2007 to 2026
$9.6M
Functional Trajectories and Illness Experiences of Older Adults with Multiple MyelomaR03AG074030 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GRANT, SHAKIRA JEANENE · 2021 to 2022
$311k
NCI NIH HHS K12 CA120780NIA NIH HHS R03 AG074030
6 · The paper itself

Abstract

backgroundDespite the increased availability and use of novel therapies for multiple myeloma, early mortality is a pervasive challenge with a significant impact on older adults. Reported rates and predictors of early mortality have varied in the literature, with most studies seldom focusing on community-treated patients.

methodsIn this retrospective cohort analysis of a real-world electronic health record-derived deidentified database of 7512 patients newly diagnosed with multiple myeloma between January 1, 2011, and February 2, 2021, and treated primarily in US-based community oncology practices, factors associated with early mortality (defined as death within 6 months after the multiple myeloma diagnosis) were examined with the use of binary logistic regression.

resultsThe median age was 70 years overall. We found an overall early mortality rate of 8.3%, with 73% of early deaths occurring in those aged ≥70 years. Among the early deaths, only 49 patients (8.7%) had documented disease progression before death (median time to progression, 30 days [interquartile range, 7-53 days]). Baseline factors associated with higher odds of early mortality included an Eastern Cooperative Oncology Group performance status (ECOG PS) ≥ 2, Revised International Staging System (R-ISS) stage III, an age ≥ 70 years, receipt of proteasome inhibitor-doublet therapy, a light-chain isotype, and the presence of renal dysfunction (estimated glomerular filtration rate < 30 mL/min). Among those aged ≥70 years, ECOG PS ≥ 2 and R-ISS stage III remained the strongest predictors of early mortality.

conclusionsEarly mortality disproportionately affects older adults (aged ≥70 years) with multiple myeloma. Interventions to support this population are needed to reduce disparate survival outcomes. PLAIN LANGUAGE SUMMARY: Factors associated with an increased risk of dying within 6 months (early mortality) of a new diagnosis of multiple myeloma (MM) among 7512 mostly community-treated patients with MM were evaluated. The early mortality rate was 8.3%; among those deaths, 49 patients (8.7%) had documented evidence of MM progression before death. The risk of early mortality was greatest for older patients (aged ≥70 years) and those with a poor performance status, poor kidney function, a higher disease stage, and light-chain MM and those receiving two-drug MM therapies. These findings highlight the need for supportive interventions geared toward older adults with MM.

Indexed as

Multiple MyelomaAgedData AnalysisDisease-Free SurvivalHumansRetrospective Studiesdeathearly mortalityelectronic health recordmultiple myelomaolder adultspredictorsreal-world experience

Identifiers

PMID36989073
PMCPMC10330042
OpenAlexW4361285724

What OpenQuestion holds

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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 OpenQuestion graph.