Cancer survivorship care in Colombia is of increasing importance. International survivorship initiatives and studies show that continuing symptoms, psychological distress, and late effects impact the quality of life for survivors. Priorities for quality survivorship according to Colombian patients and clinicians are unknown. We undertook a nominal consensus approach with 24 participants using virtual meeting technology to identify the priorities for cancer survivorship. We applied an iterative approach conducted over eight weeks with five workshops and one patient focus group followed by a priority setting survey. The consensus group established six main themes, which were subsequently evaluated by experts: (i) symptoms and secondary effects of cancer; (ii) care coordination to increase patient access and integration of cancer care; (iii) psychosocial support after cancer treatment; (iv) mapping information resources and available support services for long-term cancer care; (v) identifying socioeconomic and regional inequalities in cancer survival to improve care and outcomes; and (vi) health promotion and encouraging lifestyle change. The order of priorities differed between clinicians and patients: patients mentioned psychosocial support as the number one priority, and clinicians prioritized symptoms and surveillance for cancer recurrence. Developing survivorship care needs consideration of both views, including barriers such as access to services and socioeconomic disparities.

Prediction equations for calculating resting metabolic rate (RMR) are widely used given their accessibility and low cost. However, they have not been yet validated in the amputee athlete population. Objective: to determine the concordance between the RMR measured by Indirect Calorimetry (IC) and that calculated by prediction equations in athletes with lower limb amputation in Bogota. Subjects and methods: sixteen adult male athletes with lower limb amputation were included. The RMR was measured with IC and calculated with the Harris-Benedict, Cunningham, Mifflin-St. Jeor, Schofield, and Oxford prediction equations. Three different body mass variables were used: total body mass (TBM) and lean body mass (LBM) determined by Dual Energy X-ray Absorptiometry (DEXA) and by the anthropometric method of mass fractionation into five components (5C). The agreement was determined by intraclass correlation coefficient (ICC) and plotted using the Bland-Altman method. Results and conclusions: RMR determined by the Cunningham equation from LBM assessed by DEXA showed the best agreement with CI (ICC= 0.709), followed by Harris-Benedict with MCT (ICC= 0.697) and Cunningham with LBM calculated by 5C (ICC= 0.693). The Cunningham and Harris-Benedict equation seems to be the most suitable for calculating RMR. However, more studies with larger samples are needed to obtain more accurate results.

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