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Published on: April 5, 2024
Tumor regression dynamics with external radiotherapy in cancer cervix and its implications
N R Datta1, A Rajkumar, R Basu
1Department of Radiotherapy, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India. nrdatta@sgpgi.ac.in
Background:
To study the external radiotherapy (EXTRT) regression patterns in cancer of the cervix.
Aims:
Evaluate EXTRT tumor regression doses (TRD) for 50% (TRD50), 80% response (TRD80), normalized dose response gradient (g50) and slope (slope50) with clinical outcome.
Settings And Design:
Patients, treated solely with radiotherapy and enrolled for other prospective studies having weekly tumor regressions recorded were considered.
Material And Methods:
Seventy-seven patients received 50Gy of EXTRT at 2 Gy/fraction followed by 18Gy of high-dose rate intracavitary brachytherapy at 6 Gy/fraction. Loco-regional regressions were assessed clinically at weekly intervals during EXTRT to generate EXTRT dose-response curves.
Statistical Analysis Used:
Student's t test, logistic regression, Kaplan Meier and Cox's proportional hazard model. Scatter plots were fitted using cubic fit.
Results:
Age (P=0.052) and absence or presence of gross residual tumor (AGRT and PGRT respectively) following EXTRT (P<0.001) were the only determinants for complete response (CR) at 1 month following completion of radiotherapy. EXTRT tumor regression sigmoid curves obtained for various patient characteristics differed only for those with AGRT and PGRT with differences in TRD50, (P<0.001); TRD80 (P<0.001) and slope50 (P=0.001). Response status to EXTRT was a prognosticator for loco-regional disease free survival (LDFS) (AGRT vs. PGRT; P=0.046). On multivariate analysis, both TRD50 and TRD80 emerged as significant predictors for tumor status at end of EXTRT while TRD80 was the sole determinant of LDFS.
Conclusion:
Extent of tumor regression to EXTRT is an important predictor for treatment outcome in cancer cervix as evident from TRD50 and TRD80 values of EXTRT tumor regression curves.
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