Evidence map›Paper›PMID 39190684›Full record

ArticlePloS one2024

Developing and validating a discrete-event simulation model of multiple myeloma disease outcomes and treatment pathways using a national clinical registry.

Adam Irving, Dennis Petrie, Anthony Harris, Laura Fanning, Erica M Wood, Elizabeth Moore, Cameron Wellard, Neil Waters, Kim Huynh, Bradley Augustson and 6 more

Abstract readValidation Study
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

16 authors.

Adam IrvingCentre for Health Economics, Monash Business School, Monash University, Melbourne, Victoria, Australia.ORCID https://orcid.org/0000-0002-0406-658X
Dennis PetrieCentre for Health Economics, Monash Business School, Monash University, Melbourne, Victoria, Australia.
Anthony HarrisCentre for Health Economics, Monash Business School, Monash University, Melbourne, Victoria, Australia.
Laura FanningCentre for Health Economics, Monash Business School, Monash University, Melbourne, Victoria, Australia.
Erica M WoodTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Elizabeth MooreTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Cameron WellardTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Neil WatersTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Kim HuynhTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Bradley AugustsonSir Charles Gairdner Hospital, Perth, Western Australia, Australia.
Gordon CookLeeds Institute of Clinical Trials Research, University of Leeds, Leeds, United Kingdom.
Francesca GayDivision of Hematology, AOU Città della Salute e della Scienza di Torino, University of Turino, Torino, Italy.
Georgia McCaughanDepartment of Haematology, St Vincent's Hospital Sydney, Sydney, New South Wales, Australia.
Peter MolleePrincess Alexandra Hospital, The University of Queensland, Brisbane, Queensland, Australia.
Andrew SpencerAustralian Centre for Blood Diseases, Alfred Health-Monash University, Melbourne, Victoria, Australia.
Zoe K McQuiltenTransfusion Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma is a haematological malignancy typically characterised by neoplastic plasma cell infiltration of the bone marrow. Treatment for multiple myeloma consists of multi-line chemotherapy with or without autologous stem cell transplantation and has been rapidly evolving in recent years. However, clinical trials are unable to provide patients and clinicians with long-term prognostic information nor policymakers with the full body of evidence needed to perform economic evaluation of new therapies or make reimbursement decisions. To address these limitations of the available evidence, this study aimed to develop and validate the EpiMAP Myeloma model, a discrete-event simulation model of multiple myeloma disease outcomes and treatment pathways. Risk equations were estimated using the Australian and New Zealand Myeloma & Related Diseases Registry after multiple imputation of missing data. Risk equation coefficients were combined with multiple myeloma patients at diagnosis from the Registry to perform the simulation. The model was validated with 100 bootstraps of an out-of-sample prediction analysis using a 70/30 split of the 4,121 registry patients diagnosed between 2009 and 2023, resulting in 2,884 and 1,237 patients in the training and validation cohorts, respectively. For 90% of the 120 months in the 10-year post-diagnosis period, there was no significant difference in overall survival between the validation and simulated cohorts. These results highlight that the EpiMAP Myeloma model is robust at predicting multiple myeloma disease outcomes and treatment pathways in Australia & New Zealand. In the future, clinicians will be able to use the EpiMAP Myeloma model to provide personalised estimates of life expectancy to patients based on their specific characteristics, disease stage, and response to treatment. Policymakers will also be able to use the model to perform economic evaluation, to forecast the number of patients receiving treatment at different stages, and to determine the downstream impact of listing new, effective therapies.

Indexed as

Multiple MyelomaRegistriesAdultAgedAged, 80 and overAustraliaComputer SimulationFemaleHumansMaleMiddle AgedNew ZealandPrognosisTreatment Outcome

Identifiers

PMID39190684
PMCPMC11349175

What Socratic holds

Textmetadata
LicenceCC BY
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.