Evidence map›Paper›PMID 39192877›Full record

ArticleClinical and translational radiation oncology2024

Local relapse patterns after preoperative radiotherapy of limb and trunk wall soft tissue sarcomas: Prognostic role of imaging and pathologic response factors.

M Cuenin, A Levy, D Peiffert, M P Sunyach, A Ducassou, A Cordoba, P Gillon, D Thibouw, M Lapeyre, D Lerouge and 8 more

Abstract read
In one paragraph

Article in Clinical and translational radiation oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

18 authors.

M CueninDepartment of Radiation Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France.
A LevyDepartment of Radiation Oncology, Gustave Roussy, Thoracic Oncology Institute (IOT), Villejuif, France.
D PeiffertDepartment of Radiation Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France.
M P SunyachDepartment of Radiation Oncology, Centre Léon-Bérard, Lyon, France.
A DucassouDepartment of Radiation Oncology, IUCT-oncopole, Institut Claudius-Regaud, Toulouse, France.
A CordobaDepartment of Radiation Oncology, Centre Oscar-Lambret, Lille, France.
P GillonDepartment of Radiation Oncology, Institut Bergonié, Bordeaux, France.
D ThibouwDepartment of Radiation Oncology, Centre Régional De Lutte Contre Le Cancer Georges-François Leclerc C.G.F., Dijon, France.
M LapeyreDepartment of Radiation Oncology, Centre Jean-Perrin, Clermont-Ferrand, France.
D LerougeDepartment of Radiation Oncology, Centre François-Baclesse, Caen, France.
S HelfreDepartment of Radiation Oncology, Institut Curie, PSL Research University, Paris, France.
A LerouxDepartment of Pathology, Institut de Cancérologie de Lorraine, Vandoeuvre-les Nancy, France.
J SalleronDepartment of Statistics, Institut de Cancérologie de Lorraine, Vandoeuvre-les Nancy, France.
F SirveauxDepartment of Orthopedic Surgery, Centre Chirurgical Emile Gallé, University Hospital of Nancy, Nancy, France.
F MarchalDepartment of Surgical Oncology, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France.
P TeixeiraGuilloz Department of Imaging, Central Hospital, Nancy, France.
P A DebordesDepartment of Orthopedic Surgery, Hopitaux universitaires de Strasbourg, Strasbourg, France.
G VoginCNRS, Université de Lorraine, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To retrospectively identify clinical, pathologic, or imaging factors predictive of local relapse (LR) after preoperative radiotherapy (RT) for soft tissue sarcomas (STS). Methods and Materials: This is a retrospective multicenter study of patients who underwent preoperative RT and surgery for limb or trunk wall STS between 2007 and 2018 in French Sarcoma Group centers and were enrolled in the "Conticabase". Patterns of LR were investigated taking into account the multimodal response after preoperative RT. Diagnostic and surgical samples were compared after systematic review by expert pathologists and patients were stratified by tumor grade. Log-rank tests and Cox models were used to identify prognostic factors for radiation response and LR. Results: 257 patients were included; 17 % had low-grade (LG), 72.5 % had high-grade (HG) sarcomas. In HG group, tumors were larger, mostly undifferentiated, and displayed more necrosis and perilesional edema after RT. Median follow-up was 32 months. Five-year cumulative incidence of LR was 20.3 % in the HG group versus 9.7 % in the LG group (p = 0.026). In multivariate analysis, trunk wall location (HR 6.79, p = 0.012) and proportion of viable tumor cellularity ≥ 20 % (HR 3.15, p = 0.018) were associated with LR. After adjusting for tumor location, combination of histotype and cellularity rate significantly correlated with LR. We described three prognostic subgroups for HG sarcomas, listed from the highest to lowest risk: undifferentiated sarcoma (US) with cellularity rates ≥ 20 %; non-US (NUS) with cellularity rates ≥ 20 % or US with cellularity rates < 20 %; and NUS with cellularity rates < 20 %, which shared similar prognostic risks with LG sarcomas. Conclusions: HG and LG tumors have different morphological and biological behaviors in response to RT. Combination of cellularity rate with histotype could be a major prognostic for LR. Patients with undifferentiated HG sarcomas with cellularity rates ≥ 20 % after preoperative RT had the highest risk of LR and disease-specific death.

Indexed as

Cellularity rateGradeHistologic subtypeLocal controlSoft tissue sarcomas

Identifiers

PMID39192877
PMCPMC11347830

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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.