Tool Predicts if Seniors with Cancer Can Stay Home Post Op

Medscape

a day ago

TOPLINE:
A novel predictive model named STAYHOME effectively estimated the risk of losing the ability to live at home among older adults after cancer surgery, demonstrating good calibration with minimal deviation from observed risks. The model predicted a 2.4% and 3.4% risk for admission to a nursing home at 6 months and 12 months, respectively.
METHODOLOGY:
Older adults prioritize long-term functional independence, and the ability to return and stay at home after cancer surgery remains a key concern. However, current prognostic tools focus on short-term outcomes, lacking individualized long-term risk estimates.
To estimate the risk of losing the ability to live at home post-surgery, researchers developed and internally validated a risk prediction model, named STAYHOME, among 97,353 community-dwelling older adults (median age, 76 years) who underwent cancer surgery between 2007 and 2019.
The predictive model included preoperative variables such as age, sex, rural residence, previous cancer diagnosis, surgery type, frailty, receipt of home care support, receipt of neoadjuvant therapy, cancer site, and cancer stage.
The primary outcome was the inability to stay at home after cancer surgery, defined as the time to admission to a nursing home, and was measured at 6 months and 12 months.
TAKEAWAY:
Overall, 2658 patients (2.7%) at 6 months and 3746 (3.8%) at 12 months were admitted to a nursing home post-surgery. The mean predicted risk of not staying home was 2.4% at 6 months and 3.4% at 12 months.
The STAYHOME tool demonstrated a strong predictive capability, with areas under the curve of 0.76 and 0.75 for 6- and 12-month predictions, respectively. The tool also demonstrated minimal deviation from the observed risk for 6-month (0.33 percentage point on average; calibration slope, 1.27) and 12-month (0.46 percentage point on average; calibration slope, 1.17) predictions.
The model's calibration was excellent for most predictors at 6 months and 12 months, with a deviation of < 0.8 percentage points from the observed probability; only age older than 85 years (1.13%), preoperative frailty (1.16%), and receipt of preoperative home care support (1.25%) exceeded the deviation of 1 percentage point at 12 months.
Across risk deciles, deviations between predicted and observed probabilities were 0.1%-1.5% at 6 months and 0.1%-1.9% at 12 months, reflecting good calibration. The deviation for the slight overestimation at or above the seventh decile remained under 2% for both timepoints.
IN PRACTICE:
'The STAYHOME tool demonstrated good discrimination and was well calibrated. Thus, it may be a useful tool to identify a specific group of individuals at risk of not remaining home,' the authors wrote. '[The tool] used information readily available to patients, care partners, and healthcare professionals and may be implemented to provide them with individualized risk estimates and improve surgical oncology care delivery and experience for older adults,' they concluded.
SOURCE:
This study, led by Julie Hallet, MD, Odette Cancer Centre, Sunnybrook Health Sciences Centre in Toronto, Ontario, Canada, was published online in JAMA Surgery.
LIMITATIONS:
The STAYHOME tool showed slightly reduced discrimination for predictor levels of preoperative frailty, preoperative home care use, receipt of neoadjuvant therapy, and having stage IV disease. The model was also less well calibrated at the extremes of the risk distribution, with a slight overestimation in higher-risk categories.
DISCLOSURES:
This study was funded by operating grants from the Canadian Institutes for Health Research, Ontario Cancer Research Institute, and ICES. One author reported receiving speaker fees from Ipsen, outside the submitted work.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.