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Progression-Free Survival

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Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...

Machine learning algorithms able to predict the prognosis of gastric cancer patients treated with immune checkpoint inhibitors.

World journal of gastroenterology
BACKGROUND: Although immune checkpoint inhibitors (ICIs) have demonstrated significant survival benefits in some patients diagnosed with gastric cancer (GC), existing prognostic markers are not universally applicable to all patients with advanced GC.

Predicting benefit from PARP inhibitors using deep learning on H&E-stained ovarian cancer slides.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Ovarian cancer patients with a Homologous Recombination Deficiency (HRD) often benefit from polyadenosine diphosphate-ribose polymerase (PARP) inhibitor maintenance therapy after response to platinum-based chemotherapy. HR status is currentl...

Prognostic models for progression-free survival in atypical meningioma: Comparison of machine learning-based approach and the COX model in an Asian multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Atypical meningiomas are prevalent intracranial tumors with varied prognoses and recurrence rates. The role of adjuvant radiotherapy (ART) in atypical meningiomas remains debated. This study aimed to develop and validate a pro...

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma.

Nature communications
Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatment, leading to tumor progression and adverse outcomes in cases where complete resection is unachievable. Early prediction of treatment responsiveness...

Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer.

Oncogene
CDK4/6 inhibitors in combination with endocrine therapy are widely used to treat HR+/HER2- metastatic breast cancer leading to improved progression-free survival (PFS) compared to single agent endocrine therapy. Over 300 patients receiving standard-o...

Progression-Free Survival Prediction Performance of ChatGPT: Analysis With Real Life Data in Early and Locally Advanced Prostate Cancer.

The Prostate
OBJECTIVE: To evaluate the progression-free survival (PFS) time in patients with early-stage and locally advanced prostate cancer and to compare the estimates provided by ChatGPT with actual survival data.

A Deep Learning-Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records.

JMIR cancer
BACKGROUND: Progression-free survival (PFS) is a crucial endpoint in cancer drug research. Clinician-confirmed cancer progression, namely real-world PFS (rwPFS) in unstructured text (ie, clinical notes), serves as a reasonable surrogate for real-worl...