Evidence map›Paper›PMID 37185391›Full record

ReviewCurrent oncology (Toronto, Ont.)2023

Staging Systems and Nomograms for Soft Tissue Sarcoma.

Maria Danieli, Alessandro Gronchi

Abstract readReview
In one paragraph

Review in Current oncology (Toronto, Ont.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Review
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  6. Review
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  14. Reply to A. Mangla.JCO global oncology · 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

2 authors.

Maria DanieliDepartment of Surgery, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Giacomo Venezian, 1, 20133 Milan, Italy.
Alessandro GronchiDepartment of Surgery, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Giacomo Venezian, 1, 20133 Milan, Italy.ORCID 0000-0002-4703-3534

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new "dynamic" nomograms and prognostic tools have been developed, allowing doctors to "recalculate" a patient's prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.

Indexed as

SarcomaSoft Tissue NeoplasmsHumansNeoplasm StagingNomogramsPrognosisnomogramprognosisrecurrencesarcomasurvival

Identifiers

PMID37185391
PMCPMC10137294

What OpenQuestion holds

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Registered trials

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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.