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IntroductionLiver resection is the only curative treatment for colorectal liver metastases (CLM). Resectability decision-making is therefore a key determinant of outcomes. Wide variation has been demonstrated in resectability decision-making, despite the existence of criteria. This paper summarises a study protocol to evaluate the potential added value of two novel assessment tools in assessing CLM technical resectability: the Hepatica preoperative MR scan (MR-based volumetry, Couinaud segmentation, liver tissue characteristics and operative planning tool) and the LiMAx test (hepatic functional capacity).Methods and analysisThis study uses a systematic multistep approach, whereby three preparatory workstreams aid the design of the final international case-based scenario survey:Workstream 1: systematic literature review of published resectability criteria.Workstream 2: international hepatopancreatobiliary (HPB) interviews.Workstream 3: international HPB questionnaire.Workstream 4: international HPB case-based scenario survey.The primary outcome measures are change in resectability decision-making and change in planned operative strategy, resulting from the novel test results. Secondary outcome measures are variability in CLM resectability decision-making and opinions on the role for novel tools.Ethics and disseminationThe study protocol has been approved by a National Health Service Research Ethics Committee and registered with the Health Research Authority. Dissemination will be via international and national conferences. Manuscripts will be published.Registration detailsThe CoNoR Study is registered with ClinicalTrials.gov (registration numberNCT04270851). The systematic review is registered on the PROSPERO database (registration number CRD42019136748).

IntroductionPreoperative chemotherapy in patients undergoing resection for colorectal liver metastases (CLM) improves oncological outcomes. However, chemotherapy-associated liver injury (occurring in two patterns: vascular and fat deposition) is a real clinical concern prior to hepatic resection. After major liver resection, regeneration of the residual liver is a prerequisite for recovery and avoidance of liver failure, but this regenerative capacity may be hindered by chemotherapy. Thus, there is a need to predict for this serious complication. Over the past two decades, several tests and derived indices have been developed, which have failed to achieve clinical utility, mainly as they were indirect measurements of liver function. Here, we will use a novel test of liver function (the liver maximum capacity (LiMAx) test), and measure liver fat using MRI.Methods and analysisThis prospective study will assess changes in liver function longitudinally, measured by the LiMAx test, and liver fat, measured by advanced MRI using both MR spectroscopy and the modified Dixon method, in up to 35 patients undergoing preoperative chemotherapy for CLM. The primary outcomes will be the changes in liver function and fat compared with baseline prechemotherapy measurements. Secondary outcome measures include: routinely measured liver function blood tests, anthropometric measurements, postoperative histology and digital quantification of fat, postoperative complications and mortality and quality of life.Ethics and disseminationThe study was approved by a National Health Service Research Ethics Committee and registered with the Health Research Authority. Dissemination will be via international and national conferences and the National Institute for Health Research network. Manuscripts will be published.Trial registration numberThis study is registered online atwww.clinicaltrials.gov(registration numberNCT03562234).

Objectives Latent class trajectory modelling (LCTM) is a relatively new methodology in epidemiology to describe life-course exposures, which simplifies heterogeneous populations into homogeneous patterns or classes. However, for a given dataset, it is possible to derive scores of different models based on number of classes, model structure and trajectory property. Here, we rationalise a systematic framework to derive a ‘core’ favoured model. Methods We developed an eight-step framework: step 1: a scoping model; step 2: refining the number of classes; step 3: refining model structure (from fixed-effects through to a flexible random-effect specification); step 4: model adequacy assessment; step 5: graphical presentations; step 6: use of additional discrimination tools (‘degree of separation’; Elsensohn’s envelope of residual plots); step 7: clinical characterisation and plausibility; and step 8: sensitivity analysis. We illustrated these steps using data from the NIH-AARP cohort of repeated determinations of body mass index (BMI) at baseline (mean age: 62.5 years), and BMI derived by weight recall at ages 18, 35 and 50 years. Results From 288 993 participants, we derived a five-class model for each gender (men: 177 455; women: 111 538). From seven model structures, the favoured model was a proportional random quadratic structure (model F). Favourable properties were also noted for the unrestricted random quadratic structure (model G). However, class proportions varied considerably by model structure—concordance between models F and G were moderate (Cohen κ: men, 0.57; women, 0.65) but poor with other models. Model adequacy assessments, evaluations using discrimination tools, clinical plausibility and sensitivity analyses supported our model selection. Conclusion We propose a framework to construct and select a ‘core’ LCTM, which will facilitate generalisability of results in future studies.