
NEW YORK (Reuters Health), Dec 18 - Definitive chemoradiotherapy is an effective treatment that can be dispensed with no significant toxicity in elderly patients with locally advanced esophageal cancer, according to a 13-year study conducted at Rouen University Hospital in France.
The study included all consecutive patients older than 70 years with nonmetastatic esophageal cancer who were treated with radiation combined with cisplatin-based chemotherapy between 1994 and 2007.
Among the 109 patients analyzed, 63 (57.8%) experienced a complete clinical response, and 26 (23.8%) had no recurrence after a median follow-up of 20.5 months, Dr. David Tougeron and associates report in the November 11 issue of the British Journal of Cancer.
The median overall survival was 15.2 months, median disease-free survival was 8.3 months, and the two-year survival rate was 35.5%.
"Our results showed that chemoradiotherapy in elderly patients produced a similar response rate and overall survival as usually reported in younger patients treated with the same regimen," the authors maintain.
Although the planned protocol was given in less than half of the patients, and more than half required dose adjustments, there were only three patients with grade 4 toxicity and two treatment-related deaths. High scores on the Charlson comorbidity index were significantly associated with treatment intolerance.
In multivariate analysis, a clinical complete response, receipt of at least 80% of planned dose of radiotherapy, and a Charlson score of no greater than 2 were independent predictors of overall survival.
"In conclusion," Tougeron's group states, "definitive chemoradiotherapy could be considered as an effective treatment with no significant toxicity in elderly patients with esophageal cancer."
Br J Cancer 2008;99:1586-1592.
Last Updated: 2008-12-18 8:00:10 -0400 (Reuters Health)
Related Reading
Standard chemoradiation better for esophageal cancer, November 27, 2007
Copyright © 2008 Reuters Limited. All rights reserved. Republication or redistribution of Reuters content, including by framing or similar means, is expressly prohibited without the prior written consent of Reuters. Reuters shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon. Reuters and the Reuters sphere logo are registered trademarks and trademarks of the Reuters group of companies around the world.












![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)





