Understanding social dynamics and patient experience in out of hospital care: validation of a co-responsibility questionnaire (CoReCare).

Patient experiences are commonly assessed through patient reported experience measures (PREMs). Ambulatory care models extend traditional care into the patients' home, meaning that a triangle of health care professionals, patients, and their families need to be considered when assessing the remote care experience. These intertwined responsibilities are described by co-responsibility.

Disease progression in osteosarcoma: a multistate model for the EURAMOS-1 (European and American Osteosarcoma Study) randomised clinical trial.

Objectives: Investigating the effect of prognostic factors in a multistate framework on survival in a large population of patients with osteosarcoma. Of interest is how prognostic factors affect different disease stages after surgery, with stages of local recurrence (LR), new metastatic disease (NM), LR+NM, secondary malignancy, a second NM, and death.

Design: An open-label, international, phase 3 randomised controlled trial.

Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques.

Background: Predicting survival of recipients after liver transplantation is regarded as one of the most important challenges in contemporary medicine. Hence, improving on current prediction models is of great interest.Nowadays, there is a strong discussion in the medical field about machine learning (ML) and whether it has greater potential than traditional regression models when dealing with complex data.

Individual risk evaluation for local recurrence and distant metastasis in Ewing sarcoma: A multistate model: A multistate model for Ewing sarcoma.

Background: We investigated the effects of surgical margins, histological response, and radiotherapy on local recurrence (LR), distant metastasis (DM), and survival in Ewing sarcoma.

Procedure: Disease evolution was retrospectively studied in 982 patients with Ewing sarcoma undergoing surgery after chemotherapy using a multistate model with initial state surgery, intermediate states LR, pulmonary metastasis (DMpulm), other DM ± LR (DMother), and final state death. Effect of risk factors was estimated using Cox proportional hazard models.

Easy-to-use clinical tool for survival estimation in Ewing sarcoma at diagnosis and after surgery.

Accurate survival estimations in Ewing sarcoma are necessary to develop risk- and response adaptive treatment strategies allowing for early decision-making. We aim to develop an easy-to-use survival estimation tool from diagnosis and surgery. A retrospective study of 1314 Ewing sarcoma patients was performed.