Association of Weight Change after Colorectal Cancer Diagnosis and Outcomes in the Kaiser Permanente Northern California Population

Abstract

Background Higher body mass index (BMI) is associated with incident colorectal cancer (CRC) but not consistently with CRC survival. Whether weight gain or loss is associated with CRC survival is largely unknown. Methods We identified 2,781 patients from Kaiser Permanente Northern California diagnosed with stages I-III CRC between 2006-2011 with weight and height measurements within 3 months of diagnosis and ~18 months post diagnosis. We evaluated associations between weight change and CRC-specific and overall mortality, adjusted for sociodemographics, disease severity, and treatment. Results Following completion of treatment and recovery from stage I-III CRC, loss of at least 10% of baseline weight was associated with significantly worse CRC-specific mortality (hazard ratio [HR] 3.20; 95% confidence interval [CI], 2.33-4.39; P trend <0.0001) and overall mortality (HR 3.27; 95% CI, 2.56-4.18; P trend <0.0001). For every 5% loss of baseline weight, there was a 41% increased risk of CRC-specific mortality (95% CI, 29%-56%). Weight gain was not significantly associated with CRC-specific mortality (P trend=0.54) or overall mortality (P trend=0.27). The associations were largely unchanged after restricting analyses to exclude patients who died within 6 months and 12 months of the second weight measurement. No significant interactions were demonstrated for weight loss or gain by gender, stage, primary tumor location, or baseline BMI. Conclusions Weight loss after diagnosis was associated with worse CRC-specific mortality and overall mortality. Reverse causation does not appear to explain our findings. Impact Understanding mechanistic underpinnings for the association of weight to worse mortality is important to improving patient outcomes.

Empowering survivors after colorectal and lung cancer treatment: Pilot study of a Self-Management Survivorship Care Planning intervention

“…The following validated measures were used to assess survivor-specific outcomes: 1) Rapid Assessment of Physical Activity (RAPA) (Topolski et al, 2006); 2) Starting the Conversation (STC) for diet behaviors (Frick et al, 2017); 3) Center for Epidemiological Studies-Depression Scale (CES-D) (Knight et al, 1997); 4) State Trait Anxiety Inventory (STAI) (Meyerhardt et al, 2016); 5) Self-Efficacy to Perform Self-Management Behaviors Scale (Hershman et al, 2014); and 6) Medical Outcomes Study – Short Form-36 (SF-36) for QOL (McHorney et al, 1993). Demographics data was obtained using a self-report tool and included Instrumental Activities of Daily Living (IADL) (Fillenbaum and Smyer, 1981; Siegel et al, 2014) and perceived social support (Medical Outcomes Study Social Support Survey) (Edwards et al, 2014).…”

Non-alcoholic fatty liver disease and colorectal cancer survival

“…The Colorectal Cancer-Sarcopenia and Near-term Survival (C-SCANS) is a retrospective cohort study, which included 3,262 patients at Kaiser Permanente Northern California, aged 18–80 years, who were diagnosed with stage I–III colorectal cancer and underwent surgical resection between 2006 and 2011 [11, 12]. More detail about this cohort can be found in our previous publications [11, 12].…”

“…Data on prognostic factors (stage, treatment data, primary tumor location, and histology) were extracted from electronic medical records at KPNC and the KPNC Cancer Registry. Information on sociodemographic variables, lifestyle (e.g., smoking status), height, and weight closest to diagnosis and before treatment was also obtained via linkage to KPNC electronic medical record data [11, 12]. …”

Associations Between Dietary Patterns and Longitudinal Quality of Life Changes in Colorectal Cancer Patients: The ColoCare Study

“…The final models were adjusted for a priori selected potential confounders (sex, age, tumor stage, tumor site, and stoma). In addition, we determined changes of smoking status (never smoker, stopped smoking, still smoker, started smoking) and calculated weight change between time before surgery and 12 months after, and considered a 10% weight loss as significant (32). Within a second model, we excluded those patients with at least 10% weight loss.…”