Evidence map›Paper›PMID 27138473›Full record

ArticleClinical orthopaedics and related research2017

A Novel System for the Surgical Staging of Primary High-grade Osteosarcoma: The Birmingham Classification.

Lee M Jeys, Chris J Thorne, Michael Parry, Czar Louie L Gaston, Vaiyapuri P Sumathi, J Robert Grimer

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Article in Clinical orthopaedics and related research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
6.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 72 citations in OpenAlex.

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  11. [Primary malignant bone tumors].Orthopadie (Heidelberg, Germany) · 2023
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  13. Malignant Bone and Soft Tissue Lesions of the Foot.Journal of clinical medicine · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Lee M JeysSchool of Life and Health Sciences, Aston University, Birmingham, UK. lee.jeys@nhs.net.
Chris J ThorneSchool of Clinical and Experimental Medicine, University of Birmingham, Edgbaston, UK.
Michael ParryThe Royal Orthopaedic Hospital NHS Foundation Trust, Bristol Road South, Birmingham, B31 2AP, UK.
Czar Louie L GastonThe Royal Orthopaedic Hospital NHS Foundation Trust, Bristol Road South, Birmingham, B31 2AP, UK.
Vaiyapuri P SumathiThe Royal Orthopaedic Hospital NHS Foundation Trust, Bristol Road South, Birmingham, B31 2AP, UK.
J Robert GrimerThe Royal Orthopaedic Hospital NHS Foundation Trust, Bristol Road South, Birmingham, B31 2AP, UK.
Royal Orthopaedic Hospital · GBUniversity of Birmingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChemotherapy response and surgical margins have been shown to be associated with the risk of local recurrence in patients with osteosarcoma. However, existing surgical staging systems fail to reflect the response to chemotherapy or define an appropriate safe metric distance from the tumor that will allow complete excision and closely predict the chance of disease recurrence. We therefore sought to review a group of patients with primary high-grade osteosarcoma treated with neoadjuvant chemotherapy and surgical resection and analyzed margins and chemotherapy response in terms of local recurrence. QUESTIONS/PURPOSES: (1) What predictor or combination of predictors available to the clinician can be assessed that more reliably predict the likelihood of local recurrence? (2) Can we determine a better predictor of local recurrence-free survival than the currently applied system of surgical margins? (3) Can we determine a better predictor of overall survival than the currently applied system of surgical margins?

methodsThis retrospective study included all patients with high-grade conventional osteosarcomas without metastasis at diagnosis treated at one center between 1997 and 2012 with preoperative chemotherapy followed by resection or amputation of the primary tumor who were younger than age 50 years with minimum 24-month followup for those still alive. A total of 389 participants matched the inclusion criteria. Univariate log-rank test and multivariate Cox analyses were undertaken to identify predictors of local recurrence-free survival (LRFS). The Birmingham classification was devised on the basis of two stems: the response to chemotherapy (good response = ≥ 90% necrosis; poor response = < 90% necrosis) and margins (< 2 mm or ≥ 2 mm). The 5-year overall survival rate was 67% (95% confidence interval [CI], 61%-71%) and 47 patients developed local recurrence (12%).

resultsIntralesional margins (hazard ratio [HR], 9.9; 95% CI, 1.2-82; p = 0.03 versus radical margin HR, 1) and a poor response to neoadjuvant chemotherapy (HR, 3.8; 95% CI, 1.7-8.4; p = 0.001 versus good response HR, 1) were independent risk factors for local recurrence (LR). The best predictor of LR, however, was a combination of margins ≤ 2 mm and a less than 90% necrosis response to chemotherapy (Birmingham 2b HR, 19.6; 95% CI, 2.6-144; p = 0.003 versus Birmingham 1a; margin >2 mm and more than 90% necrosis HR, 1). Two-stage Cox regression model and higher Harrell's C statistic demonstrate that the Birmingham classification was superior to the Musculoskeletal Tumor Society (MSTS) margin classification for predicting LR (Harrell's C statistic Birmingham classification 0.68, MSTS criteria 0.59). A difference in overall survival was seen between groups of the Birmingham classification (log-rank test p < 0.0001), whereas the MSTS margin system was not discriminatory (log-rank test p = 0.14).

conclusionsBased on these observations, we believe that a combination of the recording of surgical margins in millimeters and the response to neoadjuvant chemotherapy can more accurately predict the risk of local recurrence than the current MSTS system. A multicenter collaboration study initiated by the International Society of Limb Salvage is recommended to test the validity of the proposed classification and if these findings are confirmed, this classification system might be considered the standard practice in oncology centers treating patients with osteosarcomas and allow more effective communication of margin status for research. LEVEL OF EVIDENCE: Level IV, prognostic study.

Indexed as

Amputation, SurgicalDecision Support TechniquesNeoadjuvant TherapyOsteotomyTerminology as TopicAdolescentBone NeoplasmsChemotherapy, AdjuvantDatabases, FactualDisease-Free SurvivalEnglandFemaleHumansKaplan-Meier EstimateLimb SalvageMale

Identifiers

PMID27138473
PMCPMC5289182
OpenAlexW2346962072

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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.