Modified frailty index as an indicator for outcomes after lower extremity endovascular revascularization

Balasundaram, Naveen; Kanake, Shubham; Kumar, Vishruth Thaghalli Sunil; Chandra, Isaiah; Schlesselman, Chase; Vogel, Todd R.

doi:10.1016/j.surg.2022.09.018

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…Although these indicators measurement indices represent improvements, their feasibility under the pressure of clinical work remains questionable. Therefore, the original modified frailty index (mFI-11) was modified to generate the mFI-5 by removing some variables, and the ability of mFI-5 to characterize frailty has been demonstrated in many studies (9,(21)(22)(23)(24)(25)(26)(27). Overall, frailty is an independent predictor of adverse outcomes after surgery, particular in older adults.…”

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confidence: 99%

A simplified frailty index and nomogram to predict the postoperative complications and survival in older patients with upper urinary tract urothelial carcinoma

Liu,

Wang,

et al. 2023

Front. Oncol.

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PurposeThis study was designed to investigate the clinical value of a simplified five-item frailty index (sFI) for predicting short- and long-term outcomes in older patients with upper urinary tract urothelial carcinoma (UTUC) patients after radical nephroureterectomy (RNU).MethodThis retrospective study included 333 patients (aged ≥65 years) with UTUC. Patients were classified into five groups: 0, 1, 2, 3, and 3+, according to sFI score. The variable importance and minimum depth methods were used to screen for significant variables, and univariable and multivariable logistic regression models applied to investigated the relationships between significant variables and postoperative complications. Survival differences between groups were analyzed using Kaplan-Meier plots and log-rank tests. Cox proportional hazards regression was used to evaluate risk factors associated with overall survival (OS) and cancer-specific survival (CSS). Further, we developed a nomogram based on clinicopathological features and the sFI. The area under the curve (AUC), Harrel’s concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram.ResultOf 333 cases identified, 31.2% experienced a Clavien-Dindo grade of 2 or greater complication. Random forest–logistic regression modeling showed that sFI significantly influenced the incidence of postoperative complications in older patients (AUC= 0.756). Compared with patients with low sFI score, those with high sFI scores had significantly lower OS and CSS (p < 0.001). Across all patients, the random survival forest–Cox regression model revealed that sFI score was an independent prognostic factor for OS and CSS, with AUC values of 0.815 and 0.823 for predicting 3-year OS and CSS, respectively. The nomogram developed was clinically valuable and had good ability to discriminate abilities for high-risk patients. Further, we developed a survival risk classification system that divided all patients into high-, moderate-, and low-risk groups based on total nomogram points for each patient.ConclusionA simple five-item frailty index may be considered a prognostic factor for the prognosis and postoperative complications of UTUC following RNU. By using this predictive model, clinicians may increase their accuracy in predicting complications and prognosis and improve preoperative decision-making.

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