Project description: 

Objectives: 

1) To determine and separately weight risk factors for the appearance at 12 years after surgery in patients with colon or rectal cancer of: a) death; b) readmission; c) appearance of new comorbidities and d) new tumours in other locations in these same patients.

2) To identify factors that are related to changes in quality of life at 12 years after the intervention compared to the patient’s condition before any treatment.

3) To determine differences in changes in Quality of Life, anxious-depressive symptomatology and socio-economic aspects with respect to that produced in the general test.

4) To create predictive rules for each of the previous results.

5) To describe comorbidity and quality of life in long-term colorectal cancer survivors and compare them with those without this diagnosis in order to improve and adapt the healthcare response to this group of survivors.

6) To assess the emergence of new diagnoses including psychiatric pathology and compare it with its frequency in hospital controls without cancer.

7) To assess equity issues

Methodology:

Design: This is a cohort study starting from a cohort already constituted prospectively with several FIS projects (PS09/00314 and PS09/90441; PS09/00914; PA13/00013, PI18/01181) of up to 10 years. Follow-up of these patients is proposed for up to 12 years compared to the general population. Multicentre study with 2 beneficiary centres co-ordinated with PI21/00252 and PI21/00674.

Scope: This subproject will involve four public hospitals in the Basque Country and two in Catalonia, of the 19 centres throughout Spain participating in the CARESS-CCR study.

Study subjects: Patients with colon and rectal cancer, prospectively diagnosed (new or incident cases) recruited in the CARESS-CCR study and alive in CARESS-CCR-II.

The expected impact of the results:   

In the statistical analysis with the total sample, predictive models will be created where possible predictor parameters for the outcomes to be studied will be identified. Predictive models with good discriminative capacity will be created and resampling techniques will be applied for internal validation. Generalised mixed and Cox models will be used.