European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
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Postoperative care for major elective cancer surgery is frequently provided on the Intensive Care Unit (ICU). ⋯ Elective cancer surgery represents a significant part of all ICU admissions, with a short length of stay and low mortality.
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Considering the morbidity and mortality after abdominal surgery for rectal cancer, our aim was to determine whether local excision in Stage I rectal cancer provides long-term survival equivalent to TME surgery, particularly in elderly patients. ⋯ Local excision has a poor outcome in the elderly. A negative selection bias towards old age and high co-morbidity could explain this. Hartmann's procedure has a high risk for mortality and local recurrence in younger patients.
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To construct an artificial neural network (ANN) model to predict survival after liver resection for colorectal cancer (CRC) metastases. ⋯ For the first time ANNs were used to successfully predict individual long-term survival for patients following liver resection for CRC metastases. In the future, more complex prognostic factors can be incorporated into the ANN model to increase its predictive ability.
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The aim of this study was to determine whether we could identify a subset of axillary clearance patients in whom the procedure yielded negative nodes and was therefore of no therapeutic benefit. ⋯ Preoperative ultrasound in conjunction with FNAC and clinical judgement identifies most patients with positive axillary nodes and such patients have more widespread disease. The additional value of completion axillary ANC in patients with ultrasonographically normal axillae but positive SNB appears small as sentinel node 'biopsy' serves to clear the axilla of metastases in most of these patients.
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Multicenter Study Comparative Study
Prediction of outcome in patients with urothelial carcinoma of the bladder following radical cystectomy using artificial neural networks.
The outcome of patients with urothelial carcinoma of the bladder (UCB) after radical cystectomy (RC) shows remarkable variability. We evaluated the ability of artificial neural networks (ANN) to perform risk stratification in UCB patients based on common parameters available at the time of RC. ⋯ ANN predicted tumour recurrence, CSM, and ACD in UCB patients after RC with reasonable accuracy. In this study, ANN significantly outperformed the Cox models regarding prediction of CSM and ACD using the same patients and variables. ANNs are a promising approach for individual risk stratification and may optimize individual treatment planning.