BACKGROUND: Aim of this study was to describe treatment patterns and outcome according to region and hospital type and volume among patients with rectal cancer in the Netherlands. METHODS: All patients with rectal carcinoma diagnosed in the period 2001-2006 were selected from the Netherlands Cancer Registry. Logistic regression analyses were performed to examine the influence of relevant factors on the odds of receiving preoperative radiotherapy and on the odds of postoperative mortality. Relative survival analysis was used to estimate relative excess risk of dying according to hospital type and volume. RESULTS: In total, 16 039 patients were selected. Patients diagnosed in a teaching or university hospital had a lower odds (OR 0.85; 95% CI 0.73-0.99 and OR 0.70; 95% CI 0.52-0.92) and patients diagnosed in a hospital performing >50 resections per year had a higher odds (OR 1.95; 95% CI 1.09-1.76) of receiving preoperative radiotherapy. A large variation between individual hospitals in rates of preoperative radiotherapy and between Comprehensive Cancer Centre-regions in the administration of preoperative chemoradiation was revealed. Postoperative mortality was not correlated to hospital type or volume. Patients with T1-M0 tumours diagnosed in a hospital with >50 resections per year had a better survival compared to patients diagnosed in a hospital with <25 resections per year (RER 0.11; 95% CI 0.02-0.78). CONCLUSION: This study demonstrated variation in treatment and outcome of patients with rectal cancer in the Netherlands, with differences related to hospital volume and hospitals teaching or academic status. However, variation in treatment patterns between individual hospitals proved to be much larger than could be explained by the investigated characteristics. Future studies should focus on the reasons behind these differences, which could lead to a higher proportion of patients receiving optimal treatment for their stage of the disease. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
BACKGROUND: Aim of this study was to describe treatment patterns and outcome according to region and hospital type and volume among patients with rectal cancer in the Netherlands. METHODS: All patients with rectal carcinoma diagnosed in the period 2001-2006 were selected from the Netherlands Cancer Registry. Logistic regression analyses were performed to examine the influence of relevant factors on the odds of receiving preoperative radiotherapy and on the odds of postoperative mortality. Relative survival analysis was used to estimate relative excess risk of dying according to hospital type and volume. RESULTS: In total, 16 039 patients were selected. Patients diagnosed in a teaching or university hospital had a lower odds (OR 0.85; 95% CI 0.73-0.99 and OR 0.70; 95% CI 0.52-0.92) and patients diagnosed in a hospital performing >50 resections per year had a higher odds (OR 1.95; 95% CI 1.09-1.76) of receiving preoperative radiotherapy. A large variation between individual hospitals in rates of preoperative radiotherapy and between Comprehensive Cancer Centre-regions in the administration of preoperative chemoradiation was revealed. Postoperative mortality was not correlated to hospital type or volume. Patients with T1-M0 tumours diagnosed in a hospital with >50 resections per year had a better survival compared to patients diagnosed in a hospital with <25 resections per year (RER 0.11; 95% CI 0.02-0.78). CONCLUSION: This study demonstrated variation in treatment and outcome of patients with rectal cancer in the Netherlands, with differences related to hospital volume and hospitals teaching or academic status. However, variation in treatment patterns between individual hospitals proved to be much larger than could be explained by the investigated characteristics. Future studies should focus on the reasons behind these differences, which could lead to a higher proportion of patients receiving optimal treatment for their stage of the disease. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Authors: Emily F Midura; Andrew D Jung; Meghan C Daly; Dennis J Hanseman; Bradley R Davis; Shimul A Shah; Ian M Paquette Journal: Dig Dis Sci Date: 2017-05-13 Impact factor: 3.199
Authors: Sriram Venigalla; Kevin T Nead; Ronnie Sebro; David M Guttmann; Sonam Sharma; Charles B Simone; William P Levin; Robert J Wilson; Kristy L Weber; Jacob E Shabason Journal: Int J Radiat Oncol Biol Phys Date: 2017-12-21 Impact factor: 7.038
Authors: Nikki E Kolfschoten; Perla J Marang-van de Mheen; Michel W J M Wouters; Eric-Hans Eddes; Rob A E M Tollenaar; Theo Stijnen; Job Kievit Journal: PLoS One Date: 2014-02-18 Impact factor: 3.240