Evidence map›Paper›PMID 37686671›Full record

ArticleCancers2023

Unlocking the Power of Benchmarking: Real-World-Time Data Analysis for Enhanced Sarcoma Patient Outcomes.

Bruno Fuchs, Georg Schelling, Maria Elyes, Gabriela Studer, Beata Bode-Lesniewska, Mario F Scaglioni, Pietro Giovanoli, Philip Heesen, On Behalf Of The SwissSarcomaNetwork

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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

9 authors.

Bruno FuchsSarcoma Service, University Teaching Hospital LUKS, University of Lucerne, 6000 Lucerne, Switzerland.ORCID 0000-0001-6453-3947
Georg SchellingSarcoma Service, University Teaching Hospital LUKS, University of Lucerne, 6000 Lucerne, Switzerland.
Maria ElyesSarcoma Service, University Teaching Hospital LUKS, University of Lucerne, 6000 Lucerne, Switzerland.
Gabriela StuderSarcoma Service, University Teaching Hospital LUKS, University of Lucerne, 6000 Lucerne, Switzerland.
Beata Bode-LesniewskaPatho Enge, SSN Reference Sarcoma Pathology, University of Zurich, 8000 Zurich, Switzerland.
Mario F ScaglioniSarcoma Service, University Teaching Hospital LUKS, University of Lucerne, 6000 Lucerne, Switzerland.
Pietro GiovanoliUniversity Hospital USZ, University of Zurich, 8000 Zurich, Switzerland.
Philip HeesenUniversity Hospital USZ, University of Zurich, 8000 Zurich, Switzerland.ORCID 0000-0002-5090-4935
On Behalf Of The SwissSarcomaNetwork

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Benchmarking is crucial for healthcare providers to enhance quality and efficiency, notably for complex conditions like sarcomas. Multidisciplinary teams/sarcoma boards (MDT/SBs) are vital in sarcoma management, but differences in their processes can affect patient outcomes and treatment costs, despite adherence to international guidelines. To address this issue, this study aimed to compare two MDT/SBs and establish an interoperable digital platform, Sarconnector

Indexed as

AI/ML (artificial intelligence/machine learning)CROMS (clinician-reported outcome measures)IELAS-RWTD/E (interoperable electronic longitudinal absolute structured real-world time data/evidence)IPU (integrated practice unit)MDT/SB (multidisciplinary team/sarcoma board meeting)PREMS (patient-experienced outcome measures)PROMS (patient-reported outcome measures)SPDT (sarcoma patient digital twin)VBHC (value-based healthcare)

Identifiers

PMID37686671
PMCPMC10486409

What OpenQuestion 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 OpenQuestion graph.