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Performance status is the most powerful risk factor for early death among patients with advanced soft tissue sarcoma: the European Organisation for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group (STBSG) and French Sarcoma Group (FSG) study.

Penel N, Glabbeke MV, Mathoulin-Pelissier S, Judson I, Sleijfer S, Bui B, Schoffski P, Ouali M, Marreaud S, Brouste V, Duhamel A, Hohenberger P, Blay JY - Br. J. Cancer (2011)

Bottom Line: The 90-day mortality rate was 8.6 and 4.5% in both cohorts.The CHAID analysis retained PS as a major discriminator followed by histological grade (only for patients with PS ≥2).In both models, PS was the most powerful PF for 90-day mortality.

View Article: PubMed Central - PubMed

Affiliation: Department of General Oncology, Centre Oscar Lambret, Regional Comprehensive Cancer Centre, 3, rue F Combemale, 59020, Lille, France. n-penel@o-lambret.fr

ABSTRACT

Background: We investigated prognostic factors (PFs) for 90-day mortality in a large cohort of advanced/metastatic soft tissue sarcoma (STS) patients treated with first-line chemotherapy.

Methods: The PFs were identified by both logistic regression analysis and probability tree analysis in patients captured in the Soft Tissue and Bone Sarcoma Group (STBSG) database (3002 patients). Scores derived from the logistic regression analysis and algorithms derived from probability tree analysis were subsequently validated in an independent study cohort from the French Sarcoma Group (FSG) database (404 patients).

Results: The 90-day mortality rate was 8.6 and 4.5% in both cohorts. The logistic regression analysis retained performance status (PS; odds ratio (OR)=3.83 if PS=1, OR=12.00 if PS ≥2), presence of liver metastasis (OR=2.37) and rare site metastasis (OR=2.00) as PFs for early death. The CHAID analysis retained PS as a major discriminator followed by histological grade (only for patients with PS ≥2). In both models, PS was the most powerful PF for 90-day mortality.

Conclusion: Performance status has to be taken into account in the design of further clinical trials and is one of the most important parameters to guide patient management. For those patients with poor PS, expected benefits from therapy should be weighed up carefully against the anticipated toxicities.

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Area under receiver operator curves. (A) STBSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line). (B) FSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line).
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fig2: Area under receiver operator curves. (A) STBSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line). (B) FSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line).

Mentions: Because PS appears as the most important PF in both models, we evaluated the accuracy of PS as a PF for early death (see Figure 2). In the validation cohort, the area under the receiver operator curve of PS was similar to both other models: 0.72 (0.58–0.86).


Performance status is the most powerful risk factor for early death among patients with advanced soft tissue sarcoma: the European Organisation for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group (STBSG) and French Sarcoma Group (FSG) study.

Penel N, Glabbeke MV, Mathoulin-Pelissier S, Judson I, Sleijfer S, Bui B, Schoffski P, Ouali M, Marreaud S, Brouste V, Duhamel A, Hohenberger P, Blay JY - Br. J. Cancer (2011)

Area under receiver operator curves. (A) STBSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line). (B) FSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line).
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3101912&req=5

fig2: Area under receiver operator curves. (A) STBSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line). (B) FSG database. Grey dotted line: logistic regression-based scoring; black dotted line: χ2 interaction detection algorithm; black line: performance status alone as prognostic model (this line completely covers the CHAID algorithm line).
Mentions: Because PS appears as the most important PF in both models, we evaluated the accuracy of PS as a PF for early death (see Figure 2). In the validation cohort, the area under the receiver operator curve of PS was similar to both other models: 0.72 (0.58–0.86).

Bottom Line: The 90-day mortality rate was 8.6 and 4.5% in both cohorts.The CHAID analysis retained PS as a major discriminator followed by histological grade (only for patients with PS ≥2).In both models, PS was the most powerful PF for 90-day mortality.

View Article: PubMed Central - PubMed

Affiliation: Department of General Oncology, Centre Oscar Lambret, Regional Comprehensive Cancer Centre, 3, rue F Combemale, 59020, Lille, France. n-penel@o-lambret.fr

ABSTRACT

Background: We investigated prognostic factors (PFs) for 90-day mortality in a large cohort of advanced/metastatic soft tissue sarcoma (STS) patients treated with first-line chemotherapy.

Methods: The PFs were identified by both logistic regression analysis and probability tree analysis in patients captured in the Soft Tissue and Bone Sarcoma Group (STBSG) database (3002 patients). Scores derived from the logistic regression analysis and algorithms derived from probability tree analysis were subsequently validated in an independent study cohort from the French Sarcoma Group (FSG) database (404 patients).

Results: The 90-day mortality rate was 8.6 and 4.5% in both cohorts. The logistic regression analysis retained performance status (PS; odds ratio (OR)=3.83 if PS=1, OR=12.00 if PS ≥2), presence of liver metastasis (OR=2.37) and rare site metastasis (OR=2.00) as PFs for early death. The CHAID analysis retained PS as a major discriminator followed by histological grade (only for patients with PS ≥2). In both models, PS was the most powerful PF for 90-day mortality.

Conclusion: Performance status has to be taken into account in the design of further clinical trials and is one of the most important parameters to guide patient management. For those patients with poor PS, expected benefits from therapy should be weighed up carefully against the anticipated toxicities.

Show MeSH
Related in: MedlinePlus