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1.
Artículo en Inglés | MEDLINE | ID: mdl-39255875

RESUMEN

PURPOSE: The aim of this observational, retrospective, multicenter study (Epimetheo) was to analyze the activity and the safety of SBRT during PARP inhibitors (PARPi) maintenance, in a series of oligometastatic ovarian cancer (OC) patients. METHODS: Patients treated with PARPi in maintenance setting received SBRT if oligometastatic progression occurred. Maintenance treatment was continued until the extensive progression of the disease. The primary endpoints of the study were: next systemic treatment change-free survival (NEST-FS), and acute and late toxicity; the secondary endpoints were: the rate of clinical complete response (CR), the 2-year actuarial local control (LC, progression of disease inside SBRT field) rate on "per lesion" basis, the 2-year actuarial progression free-survival (PFS), and 2-year overall survival (OS). RESULTS: From April 2018 to September 2023, SBRT was used to treat 74 OC patients with a total of 158 lesions (98 lymph nodes and 60 parenchymal lesions) under PARPi maintenance. Olaparib, Niraparib, and Rucaparib were administered to 41.9%, 48.6%, and 9.5% of patients, respectively. CR, Partial Response, Stable Disease, and Progressive Disease (PD) were observed in 115 (72.8%), 32 (20.3%), 9 (5.7%), and 2 lesions (1.3%), respectively. Severe toxicities were reported in less than 3% of patients. The actuarial median NEST-FS was 10 months, with a range of 6.7 to 13.3 months. The 12- and 24-month actuarial NEST-FS rates were 44.9% and 31.4%, respectively. The 2-year actuarial LC, PFS and OS were 68.1%, 22.5% and 77%, respectively with differences figures between complete and not complete responders. The achievement of CR was found to be correlated with an improvement in LC and OS. CONCLUSIONS: This study reports the activity and the low toxicity profile of SBRT in association with PARPi in oligometastatic OC patients. A rapid, minimally invasive, and cost-effective treatment such as SBRT may be proposed as a means of prolonging NEST-FS and maintaining an effective treatment regimen involving PARPi.

2.
Radiother Oncol ; 191: 110072, 2024 02.
Artículo en Inglés | MEDLINE | ID: mdl-38142932

RESUMEN

BACKGROUND AND PURPOSE: We aimed to develop and validate different machine-learning (ML) prediction models for the complete response of oligometastatic gynecological cancer after SBRT. MATERIAL AND METHODS: One hundred fifty-seven patients with 272 lesions from 14 different institutions and treated with SBRT with radical intent were included. Thirteen datasets including 222 lesions were combined for model training and internal validation purposes, with an 80:20 ratio. The external testing dataset was selected as the fourteenth Institution with 50 lesions. Lesions that achieved complete response (CR) were defined as responders. Prognostic clinical and dosimetric variables were selected using the LASSO algorithm. Six supervised ML models, including logistic regression (LR), classification and regression tree analysis (CART) and support vector machine (SVM) using four different kernels, were trained and tested to predict the complete response of uterine lesions after SBRT. The performance of models was assessed by receiver operating characteristic curves (ROC), area under the curve (AUC) and calibration curves. An explainable approach based on SHapley Additive exPlanations (SHAP) method was deployed to generate individual explanations of the model's decisions. RESULTS: 63.6% of lesions had a complete response and were used as ground truth for the supervised models. LASSO strongly associated complete response with three variables, namely the lesion volume (PTV), the type of lesions (lymph-nodal versus parenchymal), and the biological effective dose (BED10), that were used as input for ML modeling. In the training set, the AUCs for complete response were 0.751 (95% CI: 0.716-0.786), 0.766 (95% CI: 0.729-0.802) and 0.800 (95% CI: 0.742-0.857) for the LR, CART and SVM with a radial basis function kernel, respectively. These models achieve AUC values of 0.727 (95% CI: 0.669-0.795), 0.734 (95% CI: 0.649-0.815) and 0.771 (95% CI: 0.717-0.824) in the external testing set, demonstrating excellent generalizability. CONCLUSION: ML models enable a reliable prediction of the treatment response of oligometastatic lesions receiving SBRT. This approach may assist radiation oncologists to tailor more individualized treatment plans for oligometastatic patients.


Asunto(s)
Neoplasias , Radiocirugia , Humanos , Aprendizaje Automático , Algoritmos , Área Bajo la Curva , Respuesta Patológica Completa
3.
Clin Transl Radiat Oncol ; 34: 30-36, 2022 May.
Artículo en Inglés | MEDLINE | ID: mdl-35340685

RESUMEN

Design: Neoadjuvant chemoradiotherapy (nCRT) followed by surgery is the standard of care for locally advanced rectal cancer (LARC).Several studies have shown a correlation between a longer interval between the end of nCRT and surgery (surgical interval - SI) and an increased pathological complete response (pCR) rate, with a maximum obtained between 10 and 13 weeks.The primary endpoint of this multicenter, 2-arm randomised trial is to investigate SI lengthening, evaluating the difference in terms of complete response (CR) and Tumor Regression Grade (TRG)1 rate in the two arms. Secondly, the impact of SI lengthening on survival outcomes and quality of life (QoL) will be investigated. Methods: Intermediate-risk LARC patients undergoing nCRT will be prospectively included in the study. nCRT will be administered with a total dose of 55 Gy in 25 fractions on Gross Tumor Volume (GTV) plus the corresponding mesorectum of 45 Gy in 25 fractions on the whole pelvis. Chemotherapy with oral capecitabine will be administered continuously.The patients achieving a clinical major or complete response assessed at clinical-instrumental re-evaluation at 7-8 weeks after treatment completion, will be randomized into two groups, to undergo surgery or local excision at 9-11 weeks (control arm) or at 13-16 weeks (experimental arm). Pathological response will be assessed on the surgical specimen using the AJCC TNM v.7 and the TRG according to Mandard. Patients will be followed up to evaluate toxicity and QoL.The promoter center of the trial will conduct the randomization process through an automated procedure to prevent any possible bias.For sample size calculation, using CR difference of 20% as endpoint, 74 patients per arm will be enrolled. Conclusions: The results of this study may prospectively provide a new time frame for the clinical re-evaluation for complete/major responders patients in order to increase the CR rate to nCRT.Trial registration:ClinicalTrials.gov Identifier: NCT03581344.

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