Dataset Information

Lauren subtypes of advanced gastric cancer influence survival and response to chemotherapy: real-world data from the AGAMENON National Cancer Registry.

ABSTRACT:

Background

The choice of chemotherapy in HER2-negative gastric cancer is based on centre's preferences and adverse effects profile. No schedule is currently accepted as standard, nor are there any factors to predict response, other than HER2 status. We seek to evaluate whether Lauren type influences the efficacy of various chemotherapies and on patient overall survival (OS).

Methods

We have conducted a multicenter study in 31 hospitals. The eligibility criteria include diagnosis of stomach or gastroesophageal junction adenocarcinoma, HER2 negativity, and chemotherapy containing 2-3 drugs. Cox proportional hazards regression adjusted for confounding factors, with tests of 'treatment-by-histology' interaction, was used to estimate treatment effect.

Results

Our registry contains 1303 tumours analysable for OS end points and 730 evaluable for overall response rate (ORR). A decrease in ORR was detected in the presence of a diffuse component: odds ratio 0.719 (95% confidence interval (CI), 0.525-0.987), P=0.039. Anthracycline- or docetaxel-containing schedules increased ORR only in the intestinal type. The diffuse type displayed increased mortality with hazard ratio (HR) of 1.201 (95% CI, 1.054-1.368), P=0.0056. Patients receiving chemotherapy with docetaxel exhibited increased OS limited to the intestinal type: HR 0.65 (95% CI, 0.49-0.87), P=0.024, with no increment in OS for the subset having a diffuse component. With respect to progression-free survival (PFS), a significant interaction was seen in the effect of docetaxel-containing schedules, with better PFS limited to the intestinal type subgroup, in the comparison against any other schedule: HR 0.65 (95% CI, 0.50-0.85), P=0.015, and against anthracycline-based regimens: HR 0.64 (95% CI, 0.46-0.88), P=0.046.

Conclusions

As a conclusion, in this registry, Lauren classification tumour subtypes predicted survival and responded differently to chemotherapy. Future clinical trials should stratify effect estimations based on histology.

SUBMITTER: Jimenez Fonseca P

PROVIDER: S-EPMC5589993 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Lauren subtypes of advanced gastric cancer influence survival and response to chemotherapy: real-world data from the AGAMENON National Cancer Registry.

Jiménez Fonseca Paula P Carmona-Bayonas Alberto A Hernández Raquel R Custodio Ana A Cano Juana Maria JM Lacalle Alejandra A Echavarria Isabel I Macias Ismael I Mangas Monserrat M Visa Laura L Buxo Elvira E Álvarez Manceñido Felipe F Viudez Antonio A Pericay Carles C Azkarate Aitor A Ramchandani Avinash A López Carlos C Martinez de Castro Eva E Fernández Montes Ana A Longo Federico F Sánchez Bayona Rodrigo R Limón Maria Luisa ML Diaz-Serrano Asun A Martin Carnicero Alfonso A Arias David D Cerdà Paula P Rivera Fernando F Vieitez Jose Maria JM Sánchez Cánovas Manuel M Garrido M M Gallego J J

British journal of cancer 20170801 6

<h4>Background</h4>The choice of chemotherapy in HER2-negative gastric cancer is based on centre's preferences and adverse effects profile. No schedule is currently accepted as standard, nor are there any factors to predict response, other than HER2 status. We seek to evaluate whether Lauren type influences the efficacy of various chemotherapies and on patient overall survival (OS).<h4>Methods</h4>We have conducted a multicenter study in 31 hospitals. The eligibility criteria include diagnosis o ...[more]

PMID: 28765618

Similar Datasets

Project description:Advanced gastric cancer is one of the most thrombogenic neoplasms. However, genetic mechanisms underlying this complication remain obscure, and the molecular and histological heterogeneity of this neoplasm hinder the identification of thrombotic biomarkers. Therefore, our main objective was to identify genes related to thrombosis regardless of Lauren subtypes. Furthermore, in a secondary exploratory study, we seek to discover thrombosis-associated genes that were specific to each TCGA molecular subtype. We designed a nested case-control study using the cohort of the AGAMENON national advanced gastric cancer registry. Ninety-seven patients were selected-48 with and 49 without venous thromboembolism (using propensity score matching to adjust for confounding factors)-and a differential gene expression array stratified by Lauren histopathological subtypes was carried out in primary tumor samples. For the secondary objective, the aforementioned differential expression analysis was conducted for each TCGA group. Fifteen genes were determined to be associated with thrombosis with the same expression trend in both the intestinal and diffuse subtypes. In thrombotic subjects, CRELD1, KCNH8, CRYGN, MAGEB16, SAA1, ARL11, CCDC169, TRMT61A, RIPPLY3 and PLA2G6 were underexpressed (adjusted-p < 0.05), while PRKD3, MIR5683, SDCBP, EPS8 and CDC45 were overexpressed (adjusted-p < 0.05), and correlated, by logistic regression, with lower or higher thrombotic risk, respectively, in the overall cohort. In each TCGA molecular subtype, we identified a series of genes differentially expressed in thrombosis that appear to be subtype-specific. We have identified several genes associated with venous thromboembolism in advanced gastric cancer that are common to Lauren intestinal and diffuse subtypes. Should these genetic factors be validated in the future, they could be complemented with existing clinical models to bolster the ability to predict thrombotic risk in individuals with advanced gastric adenocarcinoma.

Project description:BackgroundPazopanib is part of the therapeutic armamentarium for the treatment of patients with advanced non-adipocytic soft tissue sarcomas (STS) who have received prior chemotherapy, but its optimal use in STS histologies is still left to be further defined.Design and methodsData on STS patients treated with pazopanib in Italy have been prospectively collected from July 2013 to December 2019 through a drug monitoring registry managed by the Italian Medicines Agency (AIFA). This nationwide observational cohort study included patients with advanced STS who received pazopanib. Clinicians were mandatorily requested to fill in the AIFA monitoring registry in order to prescribe pazopanib. Patients were recorded on the basis of their clinical characteristics, histological subtype captured at the time of treatment start, and clinical outcome. Primary outcome was time to treatment discontinuation (TTD). Secondary outcomes recorded were frequency of dose reduction and time to first dose reduction.ResultsWe analyzed data from 1964 sarcoma patients. The most represented histological subtypes were leiomyosarcoma (44.7%), undifferentiated sarcomas/not otherwise specified (11.5%), and synovial sarcoma (8.1%). Overall, the median TTD was 106 days. The variables significantly associated to shorter TTD were Eastern Cooperative Oncology Group performance status (1-2 versus 0), the number of previous lines of treatment (2-4 versus 0-1) and prescribed dose (200 mg or 400 mg versus 800 mg, all once daily). Among the most represented (>20 patients) histological subtypes, we also observed longer TTD in patients with histological diagnosis of malignant solitary fibrous tumor if compared with undifferentiated sarcoma not otherwise specified.ConclusionsIn this nationwide observational real-world study, the outcomes are similar to those reported in the pivotal trial (PALETTE study). Our study includes a significant number of patients with rare/ultra-rare sarcoma subtypes and underlines possible differences in treatment duration among these histologies.

Project description:BackgroundPreoperative prediction of the Lauren classification in gastric cancer (GC) is very important to the choice of therapy, the evaluation of prognosis, and the improvement of quality of life. However, there is not yet radiomics analysis concerning the prediction of Lauren classification straightly. In this study, a radiomic nomogram was developed to preoperatively differentiate Lauren diffuse type from intestinal type in GC.MethodsA total of 539 GC patients were enrolled in this study and later randomly allocated to two cohorts at a 7:3 ratio for training and validation. Two sets of radiomic features were derived from tumor regions and peritumor regions on venous phase computed tomography (CT) images, respectively. With the least absolute shrinkage and selection operator logistic regression, a combined radiomic signature was constructed. Also, a tumor-based model and a peripheral ring-based model were built for comparison. Afterwards, a radiomic nomogram integrating the combined radiomic signature and clinical characteristics was developed. All the models were evaluated regarding classification ability and clinical usefulness.ResultsThe combined radiomic signature achieved an area under receiver operating characteristic curve (AUC) of 0.715 (95% confidence interval [CI], 0.663-0.767) in the training cohort and 0.714 (95% CI, 0.636-0.792) in the validation cohort. The radiomic nomogram incorporating the combined radiomic signature, age, CT T stage, and CT N stage outperformed the other models with a training AUC of 0.745 (95% CI, 0.696-0.795) and a validation AUC of 0.758 (95% CI, 0.685-0.831). The significantly improved sensitivity of radiomic nomogram (0.765 and 0.793) indicated better identification of diffuse type GC patients. Further, calibration curves and decision curves demonstrated its great model fitness and clinical usefulness.ConclusionsThe radiomic nomogram involving the combined radiomic signature and clinical characteristics holds potential in differentiating Lauren diffuse type from intestinal type for reasonable clinical treatment strategy.

Dataset Information

Lauren subtypes of advanced gastric cancer influence survival and response to chemotherapy: real-world data from the AGAMENON National Cancer Registry.

Background

Methods

Results

Conclusions

Publications

Lauren subtypes of advanced gastric cancer influence survival and response to chemotherapy: real-world data from the AGAMENON National Cancer Registry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets