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The clinical use of biomarkers as prognostic factors in Ewing sarcoma.

van Maldegem AM, Hogendoorn PC, Hassan AB - Clin Sarcoma Res (2012)

Bottom Line: Good histological response (necrosis > 90%) after treatment appeared a significant predictor for a positive outcome.Our recommendation is that we can stratify patients according to their stage and using the phenotypic features of metastases, tumour size and histological response.For biological biomarkers, we suggest a number of validating studies including markers for 9p21 locus, heat shock proteins, telomerase related markers, interleukins, tumour necrosis factors, VEGF pathway, lymphocyte count, and a number of other markers including Ki-67.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Oncology University of Oxford, Oxford, OX3 7LJ, UK. bass.hassan@path.ox.ac.uk.

ABSTRACT
Ewing Sarcoma is the second most common primary bone sarcoma with 900 new diagnoses per year in Europe (EU27). It has a poor survival rate in the face of metastatic disease, with no more than 10% survival of the 35% who develop recurrence. Despite the remaining majority having localised disease, approximately 30% still relapse and die despite salvage therapies. Prognostic factors may identify patients at higher risk that might require differential therapeutic interventions. Aside from phenotypic features, quantitative biomarkers based on biological measurements may help identify tumours that are more aggressive. We audited the research which has been done to identify prognostic biomarkers for Ewing sarcoma in the past 15 years. We identified 86 articles were identified using defined search criteria. A total of 11,625 patients were reported, although this number reflects reanalysis of several cohorts. For phenotypic markers, independent reports suggest that tumour size > 8 cm and the presence of metastasis appeared strong predictors of negative outcome. Good histological response (necrosis > 90%) after treatment appeared a significant predictor for a positive outcome. However, data proposing biological biomarkers for practical clinical use remain un-validated with only one secondary report published. Our recommendation is that we can stratify patients according to their stage and using the phenotypic features of metastases, tumour size and histological response. For biological biomarkers, we suggest a number of validating studies including markers for 9p21 locus, heat shock proteins, telomerase related markers, interleukins, tumour necrosis factors, VEGF pathway, lymphocyte count, and a number of other markers including Ki-67.

No MeSH data available.


Related in: MedlinePlus

Distribution of p related to patient number for the phenotypic markers: gender, tumour size, metastases and histological response. The red line shows the cut-off point of p = 0.05.
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Figure 2: Distribution of p related to patient number for the phenotypic markers: gender, tumour size, metastases and histological response. The red line shows the cut-off point of p = 0.05.

Mentions: In this report we looked at the published data on the use of biomarkers for the last 15 years. Biomarkers were grouped into phenotypic markers and biological markers. Markers were taken as statistically significant if p < 0.05. For phenotypic markers we reported the outcome for gender, tumour size, presence of metastases and histological response after treatment (Tables 1, 2, 3 &4). We showed the p-value reported in the eligible articles and the distribution of p correlated to the number of patients (Figures 2). There doesn't seem to be a relationship between the number of patients and the p-value. For example, the distribution of histological response shows that the studies with small patient numbers have the same statistical significance as these with large patient numbers. Throughout this report, the assumption is that the biomarker has a linear relationship to outcome. We know that for many biomarkers, this is not the case. For example, data transformation using either bicubic splines or fractional polynomials is often required to correlate continuous relationships between biomarkers and outcome, as opposed to predefined cutpoints [6]. We can only have limited extrapolation of the reported data to outcome as in most instances these questions have not been addressed.


The clinical use of biomarkers as prognostic factors in Ewing sarcoma.

van Maldegem AM, Hogendoorn PC, Hassan AB - Clin Sarcoma Res (2012)

Distribution of p related to patient number for the phenotypic markers: gender, tumour size, metastases and histological response. The red line shows the cut-off point of p = 0.05.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3351700&req=5

Figure 2: Distribution of p related to patient number for the phenotypic markers: gender, tumour size, metastases and histological response. The red line shows the cut-off point of p = 0.05.
Mentions: In this report we looked at the published data on the use of biomarkers for the last 15 years. Biomarkers were grouped into phenotypic markers and biological markers. Markers were taken as statistically significant if p < 0.05. For phenotypic markers we reported the outcome for gender, tumour size, presence of metastases and histological response after treatment (Tables 1, 2, 3 &4). We showed the p-value reported in the eligible articles and the distribution of p correlated to the number of patients (Figures 2). There doesn't seem to be a relationship between the number of patients and the p-value. For example, the distribution of histological response shows that the studies with small patient numbers have the same statistical significance as these with large patient numbers. Throughout this report, the assumption is that the biomarker has a linear relationship to outcome. We know that for many biomarkers, this is not the case. For example, data transformation using either bicubic splines or fractional polynomials is often required to correlate continuous relationships between biomarkers and outcome, as opposed to predefined cutpoints [6]. We can only have limited extrapolation of the reported data to outcome as in most instances these questions have not been addressed.

Bottom Line: Good histological response (necrosis > 90%) after treatment appeared a significant predictor for a positive outcome.Our recommendation is that we can stratify patients according to their stage and using the phenotypic features of metastases, tumour size and histological response.For biological biomarkers, we suggest a number of validating studies including markers for 9p21 locus, heat shock proteins, telomerase related markers, interleukins, tumour necrosis factors, VEGF pathway, lymphocyte count, and a number of other markers including Ki-67.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Oncology University of Oxford, Oxford, OX3 7LJ, UK. bass.hassan@path.ox.ac.uk.

ABSTRACT
Ewing Sarcoma is the second most common primary bone sarcoma with 900 new diagnoses per year in Europe (EU27). It has a poor survival rate in the face of metastatic disease, with no more than 10% survival of the 35% who develop recurrence. Despite the remaining majority having localised disease, approximately 30% still relapse and die despite salvage therapies. Prognostic factors may identify patients at higher risk that might require differential therapeutic interventions. Aside from phenotypic features, quantitative biomarkers based on biological measurements may help identify tumours that are more aggressive. We audited the research which has been done to identify prognostic biomarkers for Ewing sarcoma in the past 15 years. We identified 86 articles were identified using defined search criteria. A total of 11,625 patients were reported, although this number reflects reanalysis of several cohorts. For phenotypic markers, independent reports suggest that tumour size > 8 cm and the presence of metastasis appeared strong predictors of negative outcome. Good histological response (necrosis > 90%) after treatment appeared a significant predictor for a positive outcome. However, data proposing biological biomarkers for practical clinical use remain un-validated with only one secondary report published. Our recommendation is that we can stratify patients according to their stage and using the phenotypic features of metastases, tumour size and histological response. For biological biomarkers, we suggest a number of validating studies including markers for 9p21 locus, heat shock proteins, telomerase related markers, interleukins, tumour necrosis factors, VEGF pathway, lymphocyte count, and a number of other markers including Ki-67.

No MeSH data available.


Related in: MedlinePlus