Objective: The aim of this study was to define robust benchmark values for the surgical treatment of perihilar cholangiocarcinomas (PHC) to enable unbiased comparisons. Background: Despite ongoing efforts, postoperative mortality and morbidity remains high after complex liver surgery for PHC. Benchmark data of best achievable results in surgical PHC treatment are however still lacking. Methods: This study analyzed consecutive patients undergoing major liver surgery for PHC in 24 high-volume centers in 3 continents over the recent 5-year period (2014–2018) with a minimum follow-up of 1 year in each patient. Benchmark patients were those operated at high-volume centers (≥50 cases during the study period) without the need for vascular reconstruction due to tumor invasion, or the presence of significant co-morbidities such as severe obesity (body mass index ≥35), diabetes, or cardiovascular diseases. Benchmark cutoff values were derived from the 75th or 25th percentile of the median values of all benchmark centers. Results: Seven hundred eight (39%) of a total of 1829 consecutive patients qualified as benchmark cases. Benchmark cut-offs included: R0 resection ≥57%, postoperative liver failure (International Study Group of Liver Surgery): ≤35%; in-hospital and 3-month mortality rates ≤8% and ≤13%, respectively; 3-month grade 3 complications and the CCI: ≤70% and ≤30.5, respectively; bile leak-rate: ≤47% and 5-year overall survival of ≥39.7%. Centers operating mostly on complex cases disclosed better outcome including lower post-operative liver failure rates (4% vs 13%; P = 0.002). Centers from Asia disclosed better outcomes. Conclusion: Surgery for PHC remains associated with high morbidity and mortality with now the availability of benchmark values covering 21 outcome parameters, which may serve as key references for comparison in any future analyses of individuals, group of patients or centers.

Background The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis. Analysis and Results Currently, there are no designated diagnostic or screening tests for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of ‘omics’ technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection. Conclusions Early detection may come from analytics of various body fluids (eg ‘liquid biopsies’ from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.

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