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S094: PHENOTYPIC AND VOLUMETRIC PREDICTORS OF SURGERY IN OBSERVED NONFUNCTIONING PITUITARY ADENOMAS: A COMPARATIVE ANALYSIS OF MICROADENOMAS AND MACROADENOMAS
Aarav Badani; Zain Peeran; Tej Tummala; Edward Fisher; Elaina Wang; Jacob Young; Robert C Osorio; Manish K Aghi; Department of Neurological Surgery, University of California San Francisco, San Francisco, California, United States

Introduction/Objective: Nonfunctioning pituitary adenomas (NFPAs) are managed either by observation or surgery, with tumor size frequently guiding management. We evaluated growth dynamics in observed microadenomas and macroadenomas using volumetric analyses and propensity modeling.

Methods: We retrospectively analyzed 104 patients with observed radiographically and biochemically confirmed NFPAs and ≥3 months of imaging follow-up. Tumor growth rate (mL/year) was calculated, with stability defined as no growth. Between-group comparisons were performed using Wilcoxon rank-sum testing. Effect size was quantified with Cliff’s delta. Logistic regression modeled surgical selection as a function of log-transformed initial volume, ultimate outcome at conclusion of study period (continued observation vs. switch to surgery), and their interaction.

Results: We observed 44 microadenomas (median volume=0.075 mL) and 60 macroadenomas (median volume=1.525 mL). Microadenomas had significantly lower growth rates compared with macroadenomas (median 0.003 mL/yr [0.00–0.017] vs. 0.177 mL/yr [0.00–1.104], p<0.0001). The effect size was substantial (Cliff’s delta = –0.51, 95% CI –0.67 to –0.30), indicating that in the majority of pairwise comparisons, macroadenomas grew faster than microadenomas (Figures 1A-B). Stability was observed in 43.2% of microadenomas (n=19) compared with 28.3% of macroadenomas (n=17) (Table 1). At the end of the study period, surgery was performed in 85% of macroadenomas versus 38.6% of microadenomas, after a median observation period of 35.5 months and 11.2 months, respectively (p=0.0361) (Figure 1C). The primary indication for surgery was tumor growth in 70.6% of microadenomas and 68.6% of macroadenomas (p=1.00), while patient preference accounted for 29.4% and 31.4% of cases, respectively (p=1.00).

Tumors that never underwent surgery were observed for a median of 51 months (microadenomas) and 36.6 months (macroadenomas) (p=0.221), during which time stability was observed in 51.9% of microadenomas (n=14) compared with 11.1% of macroadenomas (n=1) (p=0.051). Microadenomas that ultimately underwent surgery demonstrated higher growth rates than observed cases when stable tumors were excluded (0.05 ± 0.05 vs. 0.03 ± 0.06 mL/yr, p=0.0317). Macroadenomas that ultimately underwent surgery also presented with larger initial volumes compared with macroadenomas that were solely observed (3.84 ± 5.57 vs. 1.76 ± 2.66 mL, p=0.0365).

Logistic regression demonstrated a nonsignificant trend toward increased odds of ultimately undergoing surgery with greater initial volume (OR 1.42 [0.89–2.37], p=0.156). Macroadenomas had higher odds of ultimately going to surgery compared with microadenomas (OR 3.03 [0.64–13.88], p=0.152). No significant interaction was identified between ultimate outcome (surgery vs. continued observation) and volume (OR 1.48 [0.62–3.90], p=0.395) (Table 2). Propensity modeling demonstrated a progressive increase in surgical probability with increasing tumor volume across both phenotypes, with macroadenomas showing a higher likelihood of surgery across their observed volume range (Figure 2A-B).

Conclusion: Microadenomas frequently remained stable with minimal growth, while macroadenomas exhibited lower stability, higher growth rates, and were more often managed surgically. Cliff’s delta indicated a large effect size, with macroadenomas demonstrating substantially higher growth rates than microadenomas. Differences in growth dynamics, stability, and volume-based propensity highlight that initial tumor volume provides a practical and reproducible predictor of surgical selection. These findings strengthen the evidence base for individualized risk stratification in NFPA management.

 

 

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