Background: WHO 2022 classification underscores lineage-defining transcription factors (TFs) as key determinants of pituitary neuroendocrine tumor (PitNET) biology. We hypothesize that interaction between lineage "driver" (TFs) and proliferative "engine" (Ki-67) provides superior prognostic power for predicting recurrence compared to either factor in isolation or to traditional clinicopathological parameters.

Materials and Methods: This retrospective cohort study analyzed 302 patients who underwent primary Endoscopic Endonasal Transsphenoidal Surgery for PitNETs. Five prognostic models were constructed to simulate diverse pathology laboratory capabilities for global utility: specific TF/Ki-67 combinations (Model A), specific TFs only (B), unspecific TF multiplicity/Ki-67 (C), unspecific TF multiplicity only (D), and Ki-67 alone (E). Multivariate Cox regression, adjusted for key clinical confounders, assessed associations with recurrence.

Results: Eighty-one patients (26.82%) experienced recurrence, median follow-up: 30 months (range: 2–69). Model A & C demonstrated superior prognostic performance, identifying multiple high-risk profiles (adjusted HR [adj.HR] range: 5.36-17.70, all P<0.05). The practical Model C performed nearly equivalently to the granular Model A. Their findings were synthesized into simplified 4-tiered molecular risk stratification. Using Tier I as reference, adj.HR for recurrence escalated significantly across tiers: Model A, Tier II (adj.HR=3.65, P=0.081), Tier III (adj.HR=6.65, P=0.009), Tier IV (adj.HR=15.44, P=0.001); and Model C, Tier II (adj.HR=3.47, P=0.097), Tier III (adj.HR=6.50, P=0.010), Tier IV (adj.HR=17.78, P=0.002). In models lacking Ki-67, only SF-1(+) & T-PIT(+) (Model B, adj.HR=2.75, P=0.037) and triple-TF positivity (Models B & D, adj.HR~3.80, P=0.012) retained significance. Model E, Ki-67 ≥3% (adj.HR=1.76, P=0.015) remained significant.

Conclusion: This study validates critical prognostic synergy between TF multiplicity and elevated Ki-67 in PitNET recurrence. We propose a novel tiered molecular risk model anchored in this interaction. While this synergy is best captured by the comprehensive Model A, the full spectrum of models (A–E) provides a flexible diagnostic framework. This ensures risk stratification is accessible to pathology services with varying technical capabilities, to guide personalized post-operative management and surveillance.

Dan Taracha has completed his PhD in Neurosurgery at the age of 39 from Ningxia Medical University, China. He is set to serve as a Neurosurgeon at Bungoma County Referral Hospital, Kenya. He intends to dig deeper and do more research to make more publications in the fields of Endocrinology and Neurosurgery, increase his citation and publication h-index, and improve scientific research knowledge around the globe. He also intends to serve as an editorial board member of several reputed journals.