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Background: Colorectal neuroendocrine carcinomas (NECs), including small cell (SCNEC) and large cell (LCNEC) subtypes, are rare but aggressive malignancies with limited population-level data. Moreover, prior studies have limited stratification by histologic subtype and anatomic location, despite evidence of disease heterogeneity in colorectal malignancies. This study aimed to characterize the clinical characteristics, treatment patterns, and outcomes of colorectal NEC by histologic subtype and tumor location, and to compare them with neuroendocrine tumors (NETs) and adenocarcinomas (ACs). Methods: A retrospective cohort review was conducted utilizing the SEER database from 2000 to 2022 to identify patients with colorectal SCNEC, LCNEC, NET, and AC. Demographic, clinical, therapeutic and survival data were analyzed and compared using Kaplan–Meier methods, log-rank tests, and Cox proportional hazards regression. Results: A total of 790 SCNEC, 498 LCNEC, 31,200 NET, and 638,898 AC cases were identified. SCNEC and LCNEC were associated with advanced stage at diagnosis (66% and 55% stage IV, respectively) and inferior survival outcomes compared to NET and AC (median OS (mOS) of 7 and 8 months for SCNEC and LCNEC, respectively, p = 0.0002). Stratified by location, colonic SCNEC had the poorest survival (mOS 5 months), worse than rectal SCNEC (mOS 9 months); this pattern was not observed in LCNEC. Surgical resection was associated with improved OS in both NEC subtypes (HR range 0.25–0.56, all p < 0.012). Radiation therapy was associated with improved survival in NEC overall (SCNEC HR 0.58; LCNEC HR 0.71, both p < 0.05), with the observed benefit appearing greatest in rectal NEC. Demographic factors were associated with survival in NET and AC but had no significant impact in NEC. Conclusions: Colorectal SCNEC and LCNEC are highly aggressive malignancies with poor outcomes, with SCNEC demonstrating modestly inferior outcomes compared to LCNEC. This study demonstrates that both histologic subtype and anatomic site of disease are important determinants of prognosis and treatment response. This supports the concept that colorectal NEC represents a biologically heterogeneous disease, with colonic SCNEC showing the worst outcomes and rectal NEC associated with a potential enhanced response to radiation. These findings support the need for further prospective and molecular studies to better define treatment approaches and targeted therapies for these rare malignancies.

Background: Large language models (LLMs) are being used by surgeons for education and reference yet concerns about hallucinations and reliability limit safe adoption. Retrieval-augmented generation (RAG) can offer a potential solution by grounding responses in a high-quality external database (e.g., medical textbooks) to enhance accuracy. However, performance tradeoffs across different RAG configurations—many of which exponentially increase computational cost—remain poorly characterized. Methods: In total, 120 lightweight, open-source RAG configurations were evaluated across 40 plastic surgery-focused question-answering tasks (20 single-hop, 20 multi-hop), spanning multiple subspecialties (4800 total evaluations). Configurations varied by base LLM (Phi-3-mini-128k-instruct vs. BioMistral-7B), embedding model, database size, chunk size, and query hop type. Performance was assessed using semantic similarity (Ragas) to physician-validated reference answers. Performance was analyzed using linear mixed-effects regression with query as a random effect and fixed and interaction effects selected via likelihood testing and AIC. Results: High performance was achievable using lightweight, open-source models. While BioMistral-7B had high mean sematic similarity under specific configurations (mean semantic similarity up to 0.786), Phi-3-mini-128k-instruct demonstrated more consistent performance across query complexity. Larger database sizes significantly improved semantic similarity, with the largest gain at intermediate sizes (e.g., size 5: +0.043, p = 0.001). Embedding choice had a strong effect, with bge-large-en-v1.5 improving performance (p = 0.0016) and Bio_ClinicalBERT markedly reducing it (p < 0.001). Multi-hop queries substantially reduced performance (p < 0.001), though this effect was attenuated for Phi-3-mini-128k-instruct via a strong model × hop-type interaction (p < 0.001). Conclusions: RAG systems for plastic surgery do not require large proprietary models, as performance depends on configuration choices and interaction effects rather than isolated components. With advancements, predictive modeling may enable resource-efficient, safe deployment of clinical RAG systems.

622 Background: Colorectal small and large cell neuroendocrine carcinoma (SCNEC and LCNEC) comprise <1% of colorectal cancers and have poor prognosis. Detailed survival information is limited due to rarity. We analyzed survival outcomes using Survival, Epidemiology, and End Result (SEER) database (2000-2022) and compared with NETs and adenocarcinoma (AC). Methods: All patients with SCNEC, LCNEC, NETs or AC with colorectal primaries were extracted. AJCC stage was calculated with 8 th ed. TNM classification. Kaplan-Meier estimator, log-rank test, and Cox regression (including AJCC stage, surgery, radiation, and chemotherapy variables) were used to analyze survival outcomes. Results: Comparing colon and rectal primaries, the only significant mOS difference was in stage IV SCNEC (2 vs 7 months, p<0.0001). Comparing LCNEC and SCNEC, the only significant mOS difference was in stage IV colon SCNEC and LCNEC (2 vs 5 months, p<0.0001). Stage III and IV colorectal SCNEC and LCNEC had significantly shorter mOS than stage III and IV AC and NETs. In multivariate Cox regressions, surgery and chemotherapy were associated with significantly improved survival for both SCNEC and LCNEC at both primaries (p<0.001), while radiation was never significant. Conclusions: Most colorectal SCNEC and LCNEC patients present with stage IV disease. Stage IV colon SCNEC had significantly shorter mOS than both stage IV colon LCNEC and stage IV rectal SCNEC. Further research should explore early diagnosis and effective therapies for this rare, aggressive malignancy. Median overall survival (months) Colon SCNEC (n/mOS) Colon LCNEC (n/mOS) Colon NETs (n/mOS) Colon AC (n/mOS) SCNEC vs NETs in colon: P-value LCNEC vs NETs in colon: P-value SCNEC vs AC in colon: P-value LCNEC vs AC in colon: P-value SCNEC vs LCNEC in colon: P-value Rectal SCNEC (n/mOS) Rectal LCNEC (n/mOS) Rectal NETs (n/mOS) Rectal AC (n/mOS) SCNEC vs NETs in rectum: P-value LCNEC vs NETs in rectum: P-value SCNEC vs AC in rectum P-value LCNEC vs AC in rectum SCNEC vs LCNEC in rectum: P-value Colon SCNEC vs rectal SCNEC P-value Colon LCNEC vs rectal LCNEC: P-value Stage I 19/32 17/122 4496/NA 114,213/144 <0.0001 <0.0001 <0.0001 0.34 0.25 27/23 10/28 5185/NA 54,702/160 <0.0001 <0.0001 <0.0001 0.00047 0.88 0.99 0.24 Stage II 17/38 30/49 259/NA 121,757/106 0.0015 <0.0001 0.4 0.0068 0.65 17/16 3/NA 33/NA 38,417/106 <0.0001 0.57 <0.0001 0.87 0.3 0.065 0.55 Stage III 40/14 107/13 582/184 104,793/82 <0.0001 <0.0001 <0.0001 <0.0001 0.48 50/19 37/17 103/102 46,687/107 <0.0001 <0.0001 <0.0001 <0.0001 0.45 0.48 0.47 Stage IV 245/2 217/5 393/49 83,542/13 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 260/7 57/6 158/36 36,652/17 <0.0001 <0.0001 <0.0001 <0.0001 0.25 <0.0001 0.95

e15682 Background: Small cell carcinoma (SCC) of gastrointestinal tract is a highly aggressive rare malignancy with an estimated prevalence of 0.1% to 1% of all GI neoplasms. Treatment and survival outcomes data are very limited. Here we present an analysis of outcomes of patients with intestinal SCC using data from the Survival, Epidemiology, and End Result (SEER) database. Methods: SEER (2000-2020) was used to identify patients with SCC involving of the small intestine, colon and rectum. Variables included age, race, site, stage, chemotherapy (chemo), radiation therapy (RT) and surgery. Cox regression was used to model survival outcomes based on site, stage, and treatment received in the overall group and stage subgroups. Results: 1,169 patients with SCC of the small intestine, colon, and rectum were identified. Median age was 65 (24-90). 631 (54%) were male; majority of patients were white (989; 85%), followed by black (128; 11%) and other races (50; 4.3%). Colon (569; 49%) and rectum (514; 44%) were the predominant sites while small intestine only comprised 7.4% of the patients. Distant, regional and local diseases were reported in 55%, 17% and 7.5% of the patients. Median overall survival (mOS) of the entire group was 8 months (m). Primary tumor sites of small intestine and rectum were significantly associated with lower mortality rate in comparison to colon (11 m and 9 m vs 5 m, p < 0.001 for both). Patients with localized disease had the lowest mortality rate when compared with those with regional or distant metastatic diseases (38 m vs. 16 m and 5 m, p < 0.001 for both). Receiving surgery (HR: 0.458, p < 0.001), chemo (HR: 0.473, p < 0.001), and RT (HR: 0.733, p = 0.003) were all significantly associated with lower mortality rate (Table). These differences remained significant in each stage-based subgroup except for chemotherapy in localized disease subgroup, which encompassed only 87 patients. Conclusions: Intestinal SCC has poor prognosis, with SCC of the colon being most prevalent and with the highest mortality. Majority of patients presented with distant metastatic disease which led to high mortality. Multimodality treatment may improve survival for these patients. Number of cases (%) HR (CI) p-value mOS (months) vs reference Site (ref: colon) Rectum 514 (44%) 0.750 (0.648-0.867) <0.001 9 (ref: 5) Small intestine 86 (7.4%) 0.574 (0.44-0.749) <0.001 11 (ref: 5) Stage (ref: localized) Regional 201 (17%) 2.087 (1.507-2.891) <0.001 16 (ref: 38) Distant 639 (55%) 4.222 (3.110-5.733) <0.001 5 (ref: 38) Unknown/unstaged 242 (21%) 1.639 (1.160-2.315) 0.005 8 (ref: 38) Chemo (ref: none/unknown) Yes 590 (50%) 0.473 (0.404-0.553) <0.001 10 (ref:3) RT (ref: none/unknown) Yes 175 (15%) 0.733 (0.598-0.897) 0.003 12 (ref: 7) Surgery (ref: no surgery) Yes 363 (31%) 0.458 (0.385-0.546) <0.001 12 (ref: 6) Unknown 138 (12%) 0.717 (0.549-0.936) 0.01 7.5 (ref: 6)