Geographic and Socioeconomic Predictors of Early Follow-Up Loss in Patients Undergoing Pituitary Neuroendocrine Tumors (PITNETS) Resection: A Retrospective Review of 1143 Cases
Abstract
Objective: Postoperative follow-up after pituitary neuroendocrine tumor (PitNET) resection is critical for detecting recurrence, monitoring endocrine dysfunction, and managing surgical complications. Despite telehealth advances, early loss to follow-up persists as a barrier to care. This study aimed to identify predictors of early follow-up loss after PitNET surgery. Methods: We retrospectively analyzed 1,143 adult patients who underwent PitNET resection between 2012 and 2019 at a single tertiary neurosurgical center. Clinical, sociodemographic, and radiographic variables were collected. Loss to follow-up was defined as failure to attend a scheduled visit within 3 months postoperatively. Statistical analyses included univariate and multivariable logistic regression to determine independent predictors of early follow-up loss, along with a maximally selected log-rank statistic to identify distance thresholds associated with differences in follow-up duration. Results: Of the 1,143 patients, 131 (11.5%) were lost to follow-up within 3 months. Compared with patients with sustained follow-up, those lost were younger (median 44.0 vs. 51.0 years, p = 0.032), lived farther from the medical center (515.5 vs. 309.7 km, p = 0.024), had longer delays to surgery (148 vs. 104 days, p = 0.027), and harbored smaller tumors (1.54 vs. 1.74 cm, p = 0.04). Multivariable logistic regression identified uninsured status (OR 3.34, 95% CI 1.11–10.05, p = 0.03) and greater distance to care (OR 1.01, 95% CI 1.00–1.01, p = 0.03) as independent predictors of early loss to follow-up. A maximally selected log-rank statistic revealed 197.9 km as the optimal distance threshold, with patients living beyond this distance showing significantly shorter follow-up duration (median 17.5 vs. 24.1 months, p = 0.0012). Exploratory interaction models found no significant modification of the distance effect by race/ethnicity, employment, or English language preference. Conclusion: Early loss to follow-up after PitNET resection affects more than one in ten patients and is independently associated with lack of insurance and greater travel distance. These findings underscore the importance of identifying at-risk patients early and developing targeted interventions, such as telehealth integration and structured outreach, to ensure equitable continuity of care. Fig. 1 Geospatial distribution of PitNET patients by follow-up duration. Map of U.S. patient locations shows greater loss to follow-up among those living farther from the tertiary center, with retention clustering near the center—implicating distance as a barrier to long-term care. Basemap: Folium with CARTO and OpenStreetMap (ODbL) attributions. Fig. 2 Distance threshold and follow-up loss in PitNETs. (A) Maximally selected log-rank statistic identified 197.92 km as the optimal cutoff (M=2.95, p=0.033). (B) Kaplan–Meier curves stratified by distance: median follow-up 17.49 months (95% CI, 15.80–21.45) for >197.92 km vs 24.11 months (95% CI, 21.35–26.77) for ≤197.92 km (p=0.0012). Fig. 3 Annual trends in pituitary surgery volume and early follow-up loss. Line plot comparing the total number of pituitary surgeries performed each year (blue) with the number of patients lost to follow-up within three months postoperatively (red). While surgical volumes remained relatively stable over time, early follow-up loss varied modestly across years, suggesting potential disparities in long-term access to care despite consistent operative caseloads. Publication History Article published online: 27 February 2026 © 2026. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany
Fields of Study & Subjects
Pituitary Gland Disorders and Treatments
Neuroendocrine Tumor Research Advances
Head and Neck Surgical Oncology
Publication details
- Journal / source
- Journal of Neurological Surgery Part B Skull Base
- Volume
- 87
- Issue
- S 01
- Pages
- S1–S548
- Publication date
- 27 February 2026
- Language
- EN