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Neoadjuvant Therapy

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Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND AND PURPOSE: Current prognostic models for soft tissue sarcoma (STS) patients are solely based on staging information. Treatment-related data have not been included to date. Including such information, however, could help to improve these ...

Prediction of organ-confined disease after robot-assisted radical prostatectomy in patients with clinically locally-advanced prostate cancer.

Asian journal of surgery
BACKGROUND: Little is known about the preoperative predictive factors that could identify subsets of favorable patients who can be possibly cured with robot-assisted radical prostatectomy (RARP) alone in locally advanced prostate cancer (LAPCa). Our ...

Post prostatectomy outcomes of patients with high-risk prostate cancer treated with neoadjuvant androgen blockade.

Prostate cancer and prostatic diseases
BACKGROUND: Patients with high-risk prostate cancer have an increased likelihood of experiencing a relapse following radical prostatectomy (RP). We previously conducted three neoadjuvant androgen-deprivation therapy (ADT) trials prior to RP in unfavo...

Serum Vitamin D Levels Affect Pathologic Complete Response in Patients Undergoing Neoadjuvant Systemic Therapy for Operable Breast Cancer.

Clinical breast cancer
INTRODUCTION: There has been increasing interest in the potential benefit of vitamin D in improving breast cancer outcome. Preclinical studies suggest that vitamin D enhances chemotherapy-induced cell death. We investigated the impact of serum vitami...

Neoadjuvant endocrine treatment in early breast cancer: An overlooked alternative?

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
During the last decade neoadjuvant endocrine therapy (NET) has moved from being reserved for elderly and frail non-chemotherapy candidates to a primary systemic modality in selected patients with hormone sensitive breast cancer. Neoadjuvant hormonal ...

Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.

PloS one
Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy....

The use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery.

Techniques in coloproctology
BACKGROUND: Artificial neural networks (ANNs) can be used to develop predictive tools to enable the clinical decision-making process. This study aimed to investigate the use of an ANN in predicting the outcomes from enhanced recovery after colorectal...

Machine learning algorithms integrating positron emission tomography/computed tomography features to predict pathological complete response after neoadjuvant chemoimmunotherapy in lung cancer.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: Reliable methods for predicting pathological complete response (pCR) in non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemoimmunotherapy are still under exploration. Although Fluorine-18 fluorodeoxyglucose-positron em...

Quantitative and Morphology-Based Deep Convolutional Neural Network Approaches for Osteosarcoma Survival Prediction in the Neoadjuvant and Metastatic Settings.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep-learning strategies on histology samples to predic...