P-139 Monitoring of erlotinib plasma concentrations after long time administration of 100 mg in advanced pancreatic cancer patients

Abstract Background Most pancreatic cancer patients present with advanced stage at diagnosis with extremely short expected survival and few treatment options. A multimodal palliative approach is necessary for symptom relief and optimisation of health-related quality of life. In a recent open-label trial of mistletoe extract for advanced pancreatic cancer patients not eligible for chemotherapy, promising results on improved overall survival and better health-related quality of life were reported. The objective of the present study is to assess the value of mistletoe extract as a complement to standard 18 treatment (palliative chemotherapy or best supportive care) in advanced pancreatic cancer patients with 19 regard to overall survival and health-related quality of life. Methods The trial is prospective, randomised, double-blind, multicentre, parallel group and placebo-controlled. In total 290 participants are randomly assigned to placebo or mistletoe extract given subcutaneously in increasing dosage from 0.01mg to 20mg three times per week for nine months. Stratification is performed for site and palliative chemotherapy. Main inclusion criteria are advanced pancreatic cancer and Eastern Cooperative Oncology Group performance status zero to two; main exclusion criteria are life expectancy less than four weeks and neuroendocrine tumour of the pancreas. Two ancillary studies on sub-sets of participants are nested in the trial: a biomarker study collecting blood samples and a cross-sectional qualitative study with semi-structured face-to-face interviews. Discussion To our knowledge, this is the first placebo-controlled randomised trial assessing the impact of mistletoe extract as a complement to standard treatment on overall survival and health-related quality of life in patients with advanced pancreatic cancer. The presented trial with its two nested ancillary studies exploring biomarkers and patient experiences is expected to give new insights into the treatment of advanced pancreatic cancer. Trial registration EU Clinical Trial Register, EudraCT Number 2014-004552-64. Registered 19 January 2016, https://www.clinicaltrialsregister.eu/ctr-search/trial/2014-004552-64/SE

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Neoadjuvant radiation followed by resection versus upfront resection for locally advanced pancreatic cancer patients: a propensity score matched analysis

Oncotarget ◽

10.18632/oncotarget.18091 ◽

2017 ◽

Vol 8 (29) ◽

pp. 47831-47840 ◽

Cited By ~ 3

Author(s):

Xing Chen ◽

Geng Liu ◽

Kaiqiang Wang ◽

Guodong Chen ◽

Jinjin Sun

Keyword(s):

Pancreatic Cancer ◽

Propensity Score ◽

Cancer Patients ◽

Locally Advanced ◽

Advanced Pancreatic Cancer ◽

Locally Advanced Pancreatic Cancer

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Development and validation of a radiomics nomogram to discriminate advanced pancreatic cancer patients with liver metastases or other metastatic patterns.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.3_suppl.435 ◽

2021 ◽

Vol 39 (3_suppl) ◽

pp. 435-435

Author(s):

Junjie Hang ◽

Lixia Wu

Keyword(s):

Pancreatic Cancer ◽

Liver Metastases ◽

Cancer Patients ◽

Validation Cohort ◽

Advanced Pancreatic Cancer ◽

Region Of Interest ◽

Calibration Plot ◽

Training Cohort ◽

Kaplan Meier ◽

Metastatic Patterns

435 Background: Pancreatic cancer patients with liver metastases had much poorer prognosis than those with other metastatic patterns. This study aimed to develop and validate a radiomics model to discriminate pancreatic cancer patients with liver metastases from patients with other metastatic patterns. Methods: We evaluated 77 patients advanced pancreatic cancer (APC) with different metastatic patterns and performed texture analysis on the region of interest (ROI). 58 patients and 19 patients were allocated randomly into the training cohort and the validation cohort with almost the same proportion of patients with liver metastases. An independent samples t-test was used for initial feature selection in the training cohort. Random Forest Classifier (RFC) was used to construct models based on these features in both cohorts and a radiomics signature (RS) was derived from the model. Then a nomogram was constructed based on RS and CA19-9, and validated with calibration plot and decision curve. The prognostic value of RS was evaluated by Kaplan-Meier methods. Results: A nomogram based on the RS and CA19-9 was constructed and it demonstrated good discrimination in the training cohort (AUC = 0.93) and validation cohort (AUC = 0.81). Kaplan-meier methods showed that patients with RS>0.61 had much poorer OS than patients with RS < 0.61 in both cohorts. Conclusions:This study presents a radiomics nomogram incorporating both RS and CA19-9, which can be used to discriminate advanced pancreatic cancer patients with liver metastases from patients with other metastatic patterns.

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