View clinical trials related to Predictive Cancer Model.
Filter by:This study evaluates the clinical prognostic impact (on DFS and OS) of liquid biopsy guided treatment vs. standard of care (physicians choice) in localized pancreatic cancer (despite because of CA 19-9 levels and computed tomography, upfront surgery is recommended by tumor board). ctDNA positive patients will receive neoadjvuant chemotherapy at current gold standard physicians choice instead of upfront surgery, because of assumed high biological risk for early recurrence.
The goal of this observational study is to establish a dynamic multi-omics integration model for predicting pathological complete response (pCR) after neoadjuvant treatment in locally advanced (T3-4NxM0) rectal cancer, providing support for subsequent patient selection for the watch-and-wait strategy. The main question it aims to answer is: What is the predictive value of this model to assess individual achievement of pathological complete response (pCR) after neoadjuvant treatment? Eligible patients will be prospectively enrolled, and the clinical features of their pre-neoadjuvant treatment, during-treatment, and post-treatment preoperative will be collected and annotated.
In our prior research, a risk scoring model for the occurrence of lymph node metastasis in patients who underwent radical gastrectomy for gastric cancer was established. To further validate this scoring model, a prospective study has been designed with the aim of prospectively assessing the model's clinical applicability.
A pre-metastatic target organ/primary lesion fusion radiomics model was developed based on the "soil-seed" theory to predict comman tumor metastasis in retrospective settings. To prospectively verify the performance of the target organ/primary lesion fusion radiomics model in predicting tumor metastasis patterns (brain metastasis in lung cancer, liver metastasis in colorectal cancer, lung metastasis in breast cancer), we designed this prospective observational trial.
A previous study of investigators established a risk scoring model for the occurrence of postoperative hepatic metastases in patients who underwent curative gastrectomy directly without neoadjuvant therapy. In order to further validate the clinical applicability of abovementioned model, investigators designed this prospective study, which also included patients who received neoadjuvant therapy before surgery, with the aim of exploring the applicability of the risk scoring model to this group of patients.
Importance: Lymphovascular invasion (LVI) is a poor prognosis pathologic feature in pancreatic ductal adenocarcinoma (PDAC) patients. Neoadjuvant therapy may bring survival benefits to these patients. Objective: To construct a preoperative model which could predict LVI in PDAC patients and further validate it in other cohorts. Design, Setting, and Participants: Patients from 3 three tertiary hospitals were included in this study. Univariate and multivariate Logistic regression analyses were conducted to define independent prediction factors of LVI. A nomogram was constructed based on the result of multivariate analysis.The predictive value of the model was assessed using receiver operating characteristic (ROC) curves and the maximum Youden index of the ROC curve was defined as the cut-off point. The calibration plot was utilized to assess the concordance of the model. The decision curve analyses (DCA) were applied to estimate the clinical benefit of using this model to predict LVI.
It is known that the development of colorectal adenoma is dependent on the appearance of somatic mutations in protooncogenes and tumor suppressor genes. Based on our previous mutation analyses of 120 patients with high-risk adenoma removed by enbloc resection with subsequent colonoscopy after 1 year, there is a correlation between mutation in exon 7 of the TP53 gene and risk of early metachronous lesions development. The results also indicate that mutation phenotype (mutation profile and burden) of all lesions detected on index colonoscopy can determine risk of metachronous lesions. As not all synchronous lesions were analyzed and the surveillance colonoscopy interval was less than 3 years, this assumption could not be confirmed. In this study it is planned to perform mutation analysis of all synchronous lesions in 200 patients and correlate the data with appearance of metachronous lesions after 1, 3 and 5 years. Moreover, the mutation profile of all metachronous lesions developed during the 5 years of surveillance will be determinated and compared with mutation profile of index lesions from the same localization to verify their common biological origin. This all could help personalize the surveillance program in terms of reduction of the burden on the patient and endoscopic workplaces and risk of developing colorectal cancer in a particular patient.
The goal of this clinical trial is to assess the (cost-)effectiveness of a personalised risk assessment tool (PERSARC) to increase patients' knowledge about risks and benefits of treatment options and to reduce decisional conflict in comparison with usual care in high-grade extremity Soft-Tissue Sarcoma-patients. High-grade (2-3) extremity Soft-Tissue Sarcoma patients (>= 18 years) will either receive standard care (control group) or care with the use of PERSARC; i.e. PERSARC will be used in multidisciplinary tumour boards to guide treatment advice and in consultation in which the oncological/orthopaedic surgeon informs the patient about his/her diagnoses and discusses the benefits and harms of all relevant treatment options (intervention group)
This study will assess the ability of the Known Medicine platform to predict the efficacy of certain cancer drug treatments and to validate that tumor organoid drug sensitivity is representative of patient treatment outcomes.
It is a prospective, observational cohort study of patients with dense breast tissue. The study was based on the radiomics and other clinicopathological information of patients to establish the diagnostic system for breast disease by using artificial intelligence.