Colorectal cancer recurrence and its impact on survival after curative surgery: an analysis based on multistate models

[Abstract] Aim: To investigate the usefulness of multistate models (MSM) for determining colorectal cancer (CRC) recurrence rate, to analyse the effect of different factors on tumour recurrence and death, and to assess the impact of recurrence for CRC prognosis. Methods: Observational follow-up study of incident CRC cases disease-free after curative resection in 2006-2013 (n = 994). Recurrence and mortality were analyzed with MSM, as well as covariate effects on transition probabilities. Results: Cumulative incidence of recurrence at 60 months was 13.7%. Five years after surgery, 70.3% of patients were alive and recurrence-free, and 8.4% were alive after recurrence. Recurrence has a negative impact on prognosis, with 5-year CRC-related mortality increasing from 3.8% for those who are recurrence-free 1-year after surgery to 33.6% for those with a recurrence. Advanced stage increases recurrence risk (HR = 1.53) and CRC-related mortality after recurrence (HR = 2.35). CRC-related death was associated with age in recurrence-free patients, and with comorbidity after recurrence. As expected, age≥75 years was a risk factor for non-CRC-related death with (HR = 7.76) or without recurrence (HR = 4.26), while its effect on recurrence risk was not demonstrated. Conclusions: MSM allows detailed analysis of recurrence and mortality in CRC. Recurrence has a negative impact on prognosis. Advanced stage was a determining factor for recurrence and CRC-death after recurrence.info:eu-repo/grantAgreement/ISCIII/Programa Estatal de Fomento de la Investigación Científica y Técnica de Excelencia/PI18%2F01676/ES/CARACTERIZACIÓN DE GRANDES SUPERIVIENTES EN CANCER COLORRECTAL: APLICACIÓN DE MODELOS DE CURACIÓN PARA LA ESTIMACIÓN DE LA SUPERVIVENCIA A LARGO PLAZOThe cohort in which the study was based was recruited within the framework of a multicenter project who received two other grants from the Ministry of Science and Innovation, Carlos III Institute, Healthcare Research Fund (PI051075 and PS09/0066375)Xunta de Galicia; 08CSA073916P

Hemorragia digestiva alta secundaria a sarcoma de Kaposi gástrico y duodenal

Imágenes en patología digestiv

Characterisation of Long-Term Cancer Survivors and Application of Statistical Cure Models: A Protocol for an Observational Follow-up Study in Patients With Colorectal Cancer

Study protocol[Abstract] Background: Improved colorectal cancer (CRC) survival rates have been reported over the last years, with more than half of these patients surviving more than 5 years after the initial diagnosis. Better understanding these so-called long-term survivors could be very useful to further improve their prognosis as well as to detect other problems that may cause a significant deterioration in their health-related quality of life (HRQoL). Cure models provide novel statistical tools to better estimate the long-term survival rate for cancer and to identify characteristics that are differentially associated with a short or long-term prognosis. The aim of this study will be to investigate the long-term prognosis of CRC patients, characterise long-term CRC survivors and their HRQoL, and demonstrate the utility of statistical cure models to analyse survival and other associated factors in these patients. Methods: This is a single-centre, ambispective, observational follow-up study in a cohort of n = 1945 patients with CRC diagnosed between 2006 and 2013. A HRQoL sub-study will be performed in the survivors of a subset of n = 485 CRC patients for which baseline HRQoL data from the time of their diagnosis is already available. Information obtained from interviews and the clinical records for each patient in the cohort is already available in a computerised database from previous studies. This data includes sociodemographic characteristics, family history of cancer, comorbidities, perceived symptoms, tumour characteristics at diagnosis, type of treatment, and diagnosis and treatment delay intervals. For the follow-up, information regarding local recurrences, development of metastases, new tumours, and mortality will be updated using hospital records. The HRQoL for long-term survivors will be assessed with the EORTC QLQ-C30 and QLQ-CR29 questionnaires. An analysis of global and specific survival (competitive risk models) will be performed. Relative survival will be estimated and mixture cure models will be applied. Finally, HRQoL will be analysed through multivariate regression models. Discussion: We expect the results from this study to help us to more accurately determine the long-term survival of CRC, identify the needs and clinical situation of long-term CRC survivors, and could be used to propose new models of care for the follow-up of CRC patients.This project received a research grant from the Carlos III Institute of Health (Ministry of Science, Innovation and Universities, Spain; reference PI18/01676) which was co-funded with European Union ERDF funds (European Regional Development Fund, “A way to make Europe”). The study has undergone peer-review by the funding body. In addition, the study is also partially supported by the Galician Network for Colorectal Cancer Research (REGICC)

Clinical validation of risk scoring systems to predict risk of delayed bleeding after EMR of large colorectal lesions

[Background and Aims]: The Endoscopic Resection Group of the Spanish Society of Endoscopy (GSEED-RE) model and the Australian Colonic Endoscopic Resection (ACER) model were proposed to predict delayed bleeding (DB) after EMR of large superficial colorectal lesions, but neither has been validated. We validated and updated these models.[Methods]: A multicenter cohort study was performed in patients with nonpedunculated lesions ≥20 mm removed by EMR. We assessed the discrimination and calibration of the GSEED-RE and ACER models. Difficulty performing EMR was subjectively categorized as low, medium, or high. We created a new model, including factors associated with DB in 3 cohort studies.[Results]: DB occurred in 45 of 1034 EMRs (4.5%); it was associated with proximal location (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.31-6.16), antiplatelet agents (OR, 2.51; 95% CI, .99-6.34) or anticoagulants (OR, 4.54; 95% CI, 2.14-9.63), difficulty of EMR (OR, 3.23; 95% CI, 1.41-7.40), and comorbidity (OR, 2.11; 95% CI, .99-4.47). The GSEED-RE and ACER models did not accurately predict DB. Re-estimation and recalibration yielded acceptable results (GSEED-RE area under the curve [AUC], .64 [95% CI, .54-.74]; ACER AUC, .65 [95% CI, .57-.73]). We used lesion size, proximal location, comorbidity, and antiplatelet or anticoagulant therapy to generate a new model, the GSEED-RE2, which achieved higher AUC values (.69-.73; 95% CI, .59-.80) and exhibited lower susceptibility to changes among datasets.[Conclusions]: The updated GSEED-RE and ACER models achieved acceptable prediction levels of DB. The GSEED-RE2 model may achieve better prediction results and could be used to guide the management of patients after validation by other external groups. (Clinical trial registration number: NCT 03050333.)Research support for this study was received from “La Caixa/Caja Navarra” Foundation (ID 100010434;project PR15/11100006)

Characterisation of long-term cancer survivors and application of statistical cure models: a protocol for an observational follow-up study in patients with colorectal cancer

BACKGROUND: Improved colorectal cancer (CRC) survival rates have been reported over the last years, with more than half of these patients surviving more than 5 years after the initial diagnosis. Better understanding these so-called long-term survivors could be very useful to further improve their prognosis as well as to detect other problems that may cause a significant deterioration in their health-related quality of life (HRQoL). Cure models provide novel statistical tools to better estimate the long-term survival rate for cancer and to identify characteristics that are differentially associated with a short or long-term prognosis. The aim of this study will be to investigate the long-term prognosis of CRC patients, characterise long-term CRC survivors and their HRQoL, and demonstrate the utility of statistical cure models to analyse survival and other associated factors in these patients. METHODS: This is a single-centre, ambispective, observational follow-up study in a cohort of n = 1945 patients with CRC diagnosed between 2006 and 2013. A HRQoL sub-study will be performed in the survivors of a subset of n = 485 CRC patients for which baseline HRQoL data from the time of their diagnosis is already available. Information obtained from interviews and the clinical records for each patient in the cohort is already available in a computerised database from previous studies. This data includes sociodemographic characteristics, family history of cancer, comorbidities, perceived symptoms, tumour characteristics at diagnosis, type of treatment, and diagnosis and treatment delay intervals. For the follow-up, information regarding local recurrences, development of metastases, new tumours, and mortality will be updated using hospital records. The HRQoL for long-term survivors will be assessed with the EORTC QLQ-C30 and QLQ-CR29 questionnaires. An analysis of global and specific survival (competitive risk models) will be performed. Relative survival will be estimated and mixture cure models will be applied. Finally, HRQoL will be analysed through multivariate regression models. DISCUSSION: We expect the results from this study to help us to more accurately determine the long-term survival of CRC, identify the needs and clinical situation of long-term CRC survivors, and could be used to propose new models of care for the follow-up of CRC patients