Browsing by Author "Karyagar, Savas"
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Article The Predictive Role of Metabolic Tumor Volume on No Response To Neoadjuvant Chemotherapy in Patients With Breast Cancer(Sage Publications Ltd, 2020) Arici, Serdar; Karyagar, Sevda S.; Karyagar, Savas; Geredeli, Caglayan; Cekin, Ruhper; Secmeler, Saban; Cihan, SenerIntroduction To evaluate the predictive significance of pretreatment metabolic tumor volume on pathologic response in patients who received neoadjuvant chemotherapy for breast cancer. Methods Seventy patients who received neoadjuvant chemotherapy between 2013 and 2017 years were enrolled in the study. Pathologic responses and 18-fluorodeoxyglucose positron emission tomography/computed tomography metabolic dates of patients were obtained from archive files. Results Forty-six (65.7%) patients were in stage II and 24 (34.3%) patients were in stage III; 25 (35.7%) patients were human epidermal growth factor receptor 2 positive, 46 (65.7%) patients were estrogen receptor-positive, 26 (37.1%) patients were progesterone receptor-positive. According to the Miller-Payne grading system, 24 (34.3%) patients constituted 100% pathological response; patients with 91-99% pathological response were 12 (17.1%), the number of patients with non-pathologic response was 6 (8.6%). Median metabolic tumor volume was 7.3 cm(3) (7.1 +/- 3.5), 8.8 (11.4 +/- 9.4), 7.7 (8.3 +/- 4.6) and 22 cm(3) (19.8 +/- 11.0) in patients with stages IIA, IIB, IIIA, and IIIB, respectively (p = 0.032). In Miller-Payne grading, the median metabolic tumor volume value was higher in patients with no pathologic response group than 100% response group (p = 0.003). The cut-off metabolic tumor volume value determining no pathologic response was calculated as higher than 13.62 cm(3) (sensitivity 83.3% and specificity 82.8%). Conclusions Our study results suggest that higher pretreatment metabolic tumor volume values are predictive on no pathologic response in patients treated with neoadjuvant chemotherapy for breast cancer.Article The Predictive Value of Baseline Volumetric Pet/Ct Parameters on Treatment Response and Prognosis in Locally Advanced Rectal Cancer Treated With Neoadjuvant Chemoradiotherapy(Springer, 2022) Sakin, Abdullah; Sahin, Suleyman; Karyagar, Sevda Saglampinar; Karyagar, Savas; Atci, Mustafa; Akboru, Mustafa Halil; Cihan, SenerPurpose To investigate the prognostic effects of baseline volumetric PET/CT parameters including the maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and tumor lesion glycolysis (TLG) on treatment response and prognosis in locally advanced rectal cancer (LARC) treated with neoadjuvant chemoradiotherapy (NACRT). Methods Between 2015 and 2018, 51 patients with LARC treated with NACRT followed by surgery were included in this retrospective study. Patients were divided into 2 groups by tumor regression grade (TRG) as follows: group I = TRG 1 (no detectable cancer cells) + TRG 2 (single cells and/or small groups of cancer cells) and group II = TRG3 (residual tumor outgrown by fibrosis) + TRG 4 (remarkable fibrosis outgrown by tumor cells) + TRG 5 (no fibrosis with extensive residual cancer). Results Of the 51 patients, 34 (66.7%) were male. The median age was 55 (range, 37-78) years. According to TRG status, 14 (27.4%) patients were in group I and 37 (72.6%) patients were in group II. The area under the curve (95% CI) was 0.749 (0.593-0.905) in the ROC curve plotted for MTV. The cut-off value for MTV was 12, with 70% sensitivity and 65% specificity. MTV was >= 12 in 32 (62.8%) patients. MTV and TLG values were significantly different between groups I and II, whereas there was no significant difference between the groups in terms of SUVmax values (p = 0.006, p = 0.033, and p = 0.673, respectively). The disease-free survival was not reached in patients with MTV < 12 vs. 20 months in those with MTV >= 12 (p = 0.323). In multivariate analysis, MTV (OR, 95% Cl, 5.00 [1.17-21.383]) was found to be the factor that affected pathological complete response. Conclusion In LARC treated with NACRT, MTV prior to treatment can help predict the response to treatment.