Literature DB >> 29720389

Access to radical resections of pancreatic cancer is region-dependent despite the public healthcare system in Finland.

Reea Ahola1, Heini Hölsä2, Samuli Kiskola2, Pirkka Ojala2, Aino Pirttilä2, Juhani Sand1, Johanna Laukkarinen1,2.   

Abstract

BACKGROUND: Surgical resection is the best treatment option to improve the prognosis of pancreatic cancer (PC). Our aim was to analyse whether PC treatment strategies show regional variation in Finland, a country with a nationwide public healthcare system.
METHODS: All patients diagnosed with PC in 2003 and 2008 were identified from the Finnish Cancer Registry. The data regarding tumour, treatment, demographics and timespans to treatment were recorded from the patient archives. Patients were included in the healthcare district where the diagnosis was made. The healthcare districts were classified according to experience in pancreatic surgery into three groups (high level of experience region (HLER), n=2; medium level of experience region (MLER), n=6, and low level of experience region (LLER), n=13).
RESULTS: Patients included numbered 1546 (median age 72 years (range 34-97), 45% men). Demographics and the ratio of stage IV disease (53%) were similar between the regional groups. Despite this, the proportion of radical surgery was greater in HLERs than in the MLERs and LLERs (18% vs 8%-11%; p<0.01). Logistic regression analysis including age, American Society of Anesthesiologists classification, stage and level of experience showed that more radical resections were performed in the HLERs. Preoperative bile drainage showed no regional differences (p=0.137). Palliative chemotherapy only was used more frequently in MLER and LLER than in HLERs (24% vs 33%-30%; p<0.01).
CONCLUSION: Access to PC curative treatment was more likely for patients in healthcare districts including a hospital with high level of experience in pancreatic surgery. This highlights the importance of centralized treatment guidance. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  cancer; pancreatic cancer; public health

Year:  2018        PMID: 29720389     DOI: 10.1136/jech-2017-210187

Source DB:  PubMed          Journal:  J Epidemiol Community Health        ISSN: 0143-005X            Impact factor:   3.710


  1 in total

1.  Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection.

Authors:  Shouyun Lv; Shizong Li; Zhiwei Yu; Kaiqiong Wang; Xin Qiao; Dongwei Gong; Changxiong Wu
Journal:  J Healthc Eng       Date:  2021-09-24       Impact factor: 2.682

  1 in total

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