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PB2090: SYSTEMATIC LITERATURE REVIEW OF PROGNOSTIC FACTORS FOR RELAPSED/REFRACTORY MULTIPLE MYELOMA

2023· article· en· W4386101150 on OpenAlexaff
Shaji Kumar, Xavier Leleu, Katja Weisel, Rakesh Popat, Samantha Craigie, Leena Patel, Abril Oliva Ramirez, Wenzhen Ge, Qiufei Ma, Christian Hampp, Sundar Jagannath

Bibliographic record

VenueHemaSphere · 2023
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsMedicineInternal medicineMultiple myelomaConfidence intervalObservational studyMEDLINEOncologyMalignancyMultivariate analysisClinical trialRefractory (planetary science)Intensive care medicine

Abstract

fetched live from OpenAlex

Topic: 14. Myeloma and other monoclonal gammopathies - Clinical Background: Multiple myeloma (MM) is a highly heterogenous and incurable malignancy, with nearly all patients eventually relapsing and/or becoming refractory to treatment. Patients with relapsed and/or refractory MM (RRMM) have a poor prognosis; those who are exposed and/or refractory to multiple therapies experience even poorer outcomes. Several studies have identified factors prognostic of outcomes in patients with RRMM; however, an up-to-date synthesis of available evidence is lacking. It is important to have a systematic and evidence-based process to identify relevant prognostic factors to support MM research in a rapidly changing treatment landscape. Aims: The objective of this study was to conduct a systematic literature review (SLR) of prognostic factors associated with objective response rate (ORR), overall survival (OS), progression free survival (PFS), complete response (CR), partial response (PR), or duration of response (DOR) in patients with RRMM. Methods: Database searches were conducted in Ovid MEDLINE and Embase for clinical trials and observational studies published between January 1, 2016 and April 14, 2022. Studies were eligible if they included RRMM patients and an assessment of prognostic significance of any factor on an outcome of interest via multivariate analysis. Eligibility was assessed by two independent reviewers, with discrepancies resolved by consensus or a third independent reviewer. Data from included records were collected using standardized data extraction templates. Factors that were statistically significantly associated with an outcome of interest (p < 0.05, or confidence interval excluding the null value) were extracted. Study quality was assessed using the Quality in Prognosis Studies (QUIPS) tool. Data were summarized descriptively. Results: Of 5,349 records identified through the database and hand searches, a total of 130 records reporting on 125 unique studies were included. Twenty-three (18%) studies were clinical trials, and 102 (82%) were observational cohort studies. The most common limitations in study quality were related to sample representativeness and control of confounders. Ninety-seven factors were statistically significantly associated with at least one outcome in at least one study. The most commonly investigated factors across the 125 included studies were disease stage (n = 27 studies), age (n = 20 studies), prior lines of therapy (n = 20 studies), best response to index therapy (n = 20 studies), cytogenetic risk (n = 19 studies), lactate dehydrogenase (LDH; n = 12 studies), extramedullary disease/plasmacytoma (EMP) (n = 12 studies), and performance status (PS) (n = 10 studies). Worse survival was associated with higher disease stage, older age, more prior lines of therapy, poorer response, high-risk cytogenetics, elevated LDH levels, EMP presence, and worse PS, while worse response was associated with higher disease stage, younger age, more prior lines of therapy, high-risk cytogenetics, and worse PS. Associations between factors and outcomes were largely consistent across studies, although conflicting associations were noted in <10% of studies, and in some studies, poor reporting limited the ability to ascertain the direction of associations. Summary/Conclusion: To our best knowledge, this is the first SLR to investigate prognostic factors for an RRMM population. Using a broad approach to identify relevant studies and adhering to best practices for conducting and reporting of SLRs, this work provides a comprehensive evidence base for factors prognostic of response and survival outcomes in patients with RRMM. Keywords: Prognosis, Systematic review, relapsed/refractory, Multiple myeloma

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.320
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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