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Introduction Antibody–drug conjugates (ADCs) are now widely used in breast cancer across multiple disease subtypes. With increasing clinical use, treatment-related toxicities have become an important factor in therapeutic decision-making. However, comparative safety data among ADCs are limited because direct head-to-head trials are lacking. Methods We conducted a systematic review and Bayesian network meta-analysis of randomized controlled trials evaluating ADCs in breast cancer, with the literature search updated through March 31, 2025. Treatment-related adverse events (TRAEs) and serious adverse events (SAEs) were classified according to the Common Terminology Criteria for Adverse Events. A Bayesian random-effects network meta-analysis was used to compare toxicity risks across regimens. Odds ratios (ORs) with 95% credible intervals (CrIs) were estimated, and surface under the cumulative ranking curve (SUCRA) values were used as descriptive ranking summaries interpreted alongside the corresponding comparative estimates. The protocol was registered in PROSPERO (CRD42024606194). Results Seventeen randomized trials including 8,946 patients and five ADCs—trastuzumab emtansine (T-DM1), sacituzumab govitecan (SG), trastuzumab deruxtecan (T-DXd), datopotamab deruxtecan (Dato-DXd), and ARX788—were analyzed. SG and T-DXd showed the least favorable hematologic safety profiles, with SUCRA values for anemia/neutropenia of 22.6%/17.4% and 12.0%/27.0%, respectively. T-DM1-based regimens had the highest risk of thrombocytopenia. For gastrointestinal toxicities, SG ranked worst for diarrhea (SUCRA 6.0%), whereas T-DXd was associated with higher risks of nausea (2.2%), vomiting (7.9%), and decreased appetite (8.6%). In analyses of SAEs, SG had the highest rates of anemia (11.7%) and neutropenia (8.5%), while gastrointestinal SAEs occurred more frequently with T-DXd. Conclusions This network meta-analysis highlights clinically meaningful differences in ADC safety profiles and may help guide individualized toxicity management in breast cancer.

ABSTRACT Myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) are clonal myeloid neoplasms shaped by genetic lesions and immune dysregulation, both of which contribute to disease progression and poor outcomes. Existing prognostic systems, such as IPSS‐R and IPSS‐M, do not incorporate immune alterations. We assessed the biological and clinical relevance of an immune dysfunction signature (IDS) across multi‐center MDS and CMML cohorts. IDS scores, derived from bulk transcriptomic data, were significantly associated with inferior leukemia‐free and overall survival. In multivariable analyses, IDS retained independent prognostic value alongside IPSS‐R, IPSS‐M, and bi‐allelic TP53 inactivation. Incorporation of IDS into existing models improved prognostic discrimination and time‐dependent predictive accuracy. Longitudinal analyses revealed that rising IDS scores paralleled disease progression and acute transformation, whereas declining scores were observed in remission. Biologically, IDS‐high cases demonstrated reduced cytotoxic T‐cell activity, expansion of regulatory T cells, enrichment of primitive progenitor signals, and increased expression of checkpoint pathway genes. These findings were validated across multiple independent MDS cohorts and consistently reproduced in CMML, where IDS also stratified risk and tracked disease evolution. Finally, integration with drug response signatures from the BeatAMLv2 cohort suggested potential therapeutic vulnerability of IDS‐high cases to multikinase and NF‐κB pathway inhibitors. These results establish IDS as a robust and dynamic biomarker in MDS and CMML, with applications in refined risk stratification, longitudinal disease monitoring, and guiding personalized therapeutic strategies targeting immune dysfunction. Trial Registration: #201709072RINC, #202109078RINB, #202207050RINB

Abstract Prognostic indices such as the CLL International Prognostic Index (CLL-IPI) and the International Prognostic Score for Early-stage CLL (IPS-E) can predict time to first treatment (TTFT) in patients with early-stage CLL. Their ability to predict risk of infection - a leading contributor to morbidity and mortality in CLL - remains uncertain. The CLL-TIM is a machine-learning model developed in Europe that integrates clinical, laboratory, and infection-related data to predict TTFT or infection risk within 2-years of diagnosis, Receiver Operating Characteristic - Area Under the Curve (ROC-AUC) 0.74; Agius et al., Nat Comm 11, 363 2020. We conducted the first validation of CLL-TIM in a US cohort of newly diagnosed CLL patients and compared its performance with the CLL-IPI and IPS-E indices. Adults with newly diagnosed CLL (2000-2020) were identified through the Rochester Epidemiology Project using International Classification of Disease (ICD) codes; all diagnoses were confirmed. We replicated the variable selection from the original CLL-TIM model and applied it to our cohort. The primary endpoint was a 2-year composite of either TTFT or incident infection (defined as having blood cultures drawn). Model performance was evaluated using ROC-AUC consistent with the original CLL-TIM methods. CLL-IPI and IPS-E performance was assessed using time-dependent ROC-AUC; pairwise differences in discrimination were tested using DeLong. We identified 454 CLL patients with a median age of 72 years [range, 30-97], 166 (37%) were female, Rai Stage was 0-II in 399 (92%) patients. IGHV genes were unmutated in 130/305 (42%) patients and TP53 disruption (either del17p by FISH or TP53 mutation) was present in 24/329 (8%) patients. At 2-years, 55 (12%) patients received CLL therapy, and 56 (12%) patients had an infection. The 2-year composite endpoint was observed in 94 (21%) patients. The ROC-AUC was 0.74 (95% CI 0.68-0.80) for CLL-TIM, 0.69 for CLL-IPI (95% CI 0.63-0.75, p=0.11 compared to CLL-TIM) , and 0.68 for IPS-E (95% CI 0.62-0.74, p=0.02 compared to CLL-TIM). We also evaluated the ROC-AUC using all the prognostic models for each individual endpoints. The corresponding ROC-AUC for TTFT at 2 years were 0.79, 0.74, and 0.76 for CLL-TIM, CLL-IPI, and IPS-E, respectively; and for infection at 2 years were 0.68, 0.57, and 0.52, respectively. This is the first validation of the CLL-TIM in a US-based cohort of newly diagnosed CLL patients. Although the CLL-TIM model exceeded the minimally meaningful discrimination threshold (AUC >0.7) for individual patient-level risk prediction, there was no statistical difference in AUC between CLL-TIM and CLL-IPI, suggesting either model can predict the composite endpoint at 2 years. Most of the observed discrimination was driven by prediction of TTFT rather than infection, underscoring the need to develop more infection-specific risk models for newly diagnosed CLL. Citation Format: Raphael Mwangi, Tait D. Shanafelt, Soren Basnet, Emily L. West, Owen Keegan, Timothy G. Call, Yao Yuan, Bryan Alexis Vallejo, Paul J. Hampel, Lindsey E. Roeker, Yucai Wang, Saad J. Kenderian, Sara J. Achenbach, Aaron D. Norman, Kari G. Rabe, Neil E. Kay, James R. Cerhan, Curtis A. Hanson, Susan L. Slager, Sameer A. Parikh. Validation of the CLL treatment infection model (CLL-TIM) in patients with newly diagnosed chronic lymphocytic leukemia (CLL) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 4228.

Abstract Background: Hypogammaglobulinemia at the time of CLL diagnosis predicts shorter time to first therapy (TTFT). However, the depth of immunoparesis and its impact on TTFT in newly diagnosed MBL/CLL remains unexplored. Methods: We identified previously untreated MBL/CLL patients from Mayo Clinic CLL Database (2000-2024) who had serum immunoglobulin (Ig; IgG, IgM and IgA) and monoclonal protein assessed within 1 year of diagnosis. Immunoparesis was evaluated: a) qualitatively by classifying patients into preserved, partial and full Ig suppression, based on the number of suppressed Igs; and b) quantitatively by calculating the average relative difference (ARD), defined as the mean percentage below normal for all Igs. For both methods, only uninvolved Igs were considered for those with monoclonal protein. TTFT was estimated by Kaplan-Meier with competing risk of death. Cox models estimated hazard ratios (HR) and 95% confidence intervals (CI). Results: Among 1420 patients, median age at diagnosis was 65 (range 28-96); 954 (67%) were male; 493 (44.8%) had unmutated IGHV, and 86 (6.8%) had TP53 disruption. The median [range, mg/dL] serum IgG, IgA, and IgM were 889 [111-5290], 132 [1-4880], and 49 [4-9480]. Low IgG was present in 472 (33.2%), low IgA in 223 (16.4%), and low IgM in 530 (37.3%) patients. An M-spike was detected in 122 (8.6%) patients; distribution was: IgG (73), IgM (30), IgA (6), or multiple (13). By qualitative assessment, preserved Ig were seen in 664 (46.8%), partial Ig suppression in 604 (42.5%), and full suppression in 152 (10.7%) patients. By quantitative assessment, median ARD was 0.6 (-0.8 to 11.3); 280 (19.7%) patients had negative ARD, and 1140 (80.3%) had positive ARD. In those with negative ARD, 128 (9%) had partial Ig suppression and 152 (10.7%) had full Ig suppression; in those with positive ARD, 664 (46.8%) had preserved Ig and 476 (33.5%) had partial Ig suppression. Median follow-up was 14.7 years; 510 patients progressed requiring therapy. Median TTFT was 9.6 years. Median TTFT for patients with preserved Ig was 12.6 years, 8.0 years for partial Ig suppression (HR 1.4, 95%CI 1.1-1.7), and 1.8 years for full Ig suppression (HR 3.1, 95%CI 2.4-4.0). The median TTFT was 2.3 and 12.1 years for patients with negative vs positive ARD; negative ARD was associated with shorter TTFT (HR 2.4, 95%CI 2.0-2.9). After adjusting for sex and CLL-International Prognostic Index (CLL-IPI) score, full Ig suppression (HR 2.9, 95%CI 2.2-3.9) and partial Ig suppression (HR 1.6, 95% CI 1.3-2.0) were associated with shorter TTFT (model 1, c-stat 0.77); and negative ARD (HR 2.4, 95%CI 2.0-2.9) was associated with shorter TTFT (model 2, c-stat 0.76). Negative ARD identified an additional 9% of patients at higher risk for shorter TTFT beyond full Ig suppression. Conclusions: The depth of immunoparesis at diagnosis predicts TTFT and enhances risk stratification in newly diagnosed MBL/CLL. Citation Format: Yuan Yao, Kari G. Rabe, Eli Muchtar, Paul Hampel, Yucai Wang, Lindsey Roeker, Saad Kenderian, Amber Koehler, Catherine Wagner, Amy Behnken, Jose F. Leis, Mazie Tsang, Talal Hilal, Ricardo Daniel Parrondo, Susan M. Schwager, Min Shi, Curtis A. Hanson, Celine M. Vachon, Shaji Kunnathu Kumar, Esteban Braggio, Neil E. Kay, Susan Slager, Sameer A. Parikh. Depth of immunoparesis predicts time to first therapy in newly diagnosed monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1191.

PURPOSE Chronic myelomonocytic leukemia (CMML) is a rare myeloid neoplasm characterized by clinical heterogeneity and is associated with poor outcomes. To date, limited molecular information has been incorporated into disease classification and risk stratification. We aimed to integrate genomic features into the clinical decision-making process for CMML. PATIENTS AND METHODS We analyzed a retrospective cohort of 3013 patients with CMML (training set) and a prospective population of 516 patients (validation set). Using an innovative framework for multimodal data analysis, we developed molecular-based disease taxonomy and prognostication. RESULTS Unsupervised clustering identified nine entities with distinct genomic features and outcomes ( P < .001), including splicing machinery, transcription factors, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures. Notably, 15% of patients showed molecular/clinical overlap with other myeloid neoplasms. We integrated molecular and clinical information to build the international CMML Prognostic Scoring System (iCPSS), incorporating mutations in nine genes together with hematologic parameters and cytogenetic abnormalities. The iCPSS identified five groups with distinct probability of overall and leukemia-free survival in both training and validation cohorts ( P < .001), outperforming existing prognostic models. Importantly, 55% of patients were reassigned to higher or lower risk groups by the iCPSS. Decision analysis demonstrated that iCPSS could refine the optimal timing of allogeneic transplantation at the individual level; compared with conventional prognostic tools, iCPSS-based decision modeling changed transplantation strategy in 31% of cases, resulting in a significant gain-in-life expectancy for eligible patient population ( P < .001). A federated learning platform was implemented to enable continuous, privacy-preserving model update across multiple centers. CONCLUSION Molecular information improves CMML classification and prognostication, supports more effective clinical decision making, and potentially refines the design of clinical trials.

Abstract Background: Monoclonal B-cell lymphocytosis (MBL), a precursor to chronic lymphocytic leukemia (CLL), is an understudied yet common premalignant condition present in ~8 million adults in the United States. Based on flow cytometry, MBL can be classified into two immunophenotypes: CLL-type (CD5, CD23, and CD20 co-expression) and non-CLL-type (CD5-negative). While the majority of the data to date pertains to CLL-type MBL, the available evidence indicates non-CLL-type MBL is also associated with an increased risk of hematologic malignancies. Clonal hematopoiesis of indeterminate potential (CHIP) is another precursor condition associated with hematologic malignancies. The relationship between non-CLL-type MBL and CHIP and their combined effect remains unknown. Herein, we report findings on these two precursor conditions in the largest screening cohort to date. Methods: Using flow cytometry, we screened for MBL in the Mayo Clinic Biobank participants who were 40 years or older with no prior history of hematologic cancers. Using whole-exome sequencing of whole-blood DNA, CHIP was screened on 291 genes related to myeloid (56 genes) or lymphoid malignancies (235 genes). Incident hematologic malignancies were detected during follow-up using International Classification of Diseases (ICD) codes in the medical record. All diagnoses were manually reviewed for confirmation. Multivariable logistic regression was used to evaluate the association between non-CLL-type MBL and CHIP. Time to incident hematologic malignancy was calculated from date of MBL screening to the earliest date of incident malignancy, withdrawal, death, last medical visit, or study end. Overall survival (OS) was calculated from date of MBL screening to date of death or last known alive. Multivariable Cox regression, adjusted for age, sex and residency, was used to investigate associations between non-CLL-type MBL and CHIP with clinical outcomes; with results reported using hazard ratios (HR) and 95% confidence intervals (CI). Results: In total, 8,802 individuals with MBL screening and CHIP data were analyzed. Non-CLL-type MBL was detected in 249 (2.8%) individuals; 121 (49%) were male, and median age was 78 years (range, 47-95). We identified 757 (8.6%) individuals with CHIP in at least one of the 291 genes tested. The most frequently mutated CHIP genes were DNMT3A, TET2, ASXL1, PPM1D, and TP53. A total of 47 (0.5%) individuals had both non-CLL-type MBL and CHIP; the four genes with the highest number of CHIP variants in these individuals were DNMT3A (n=16), TET2 (n=10), ASXL1 (n=3), and ATM (n=3). An association between non-CLL-type MBL and any CHIP (OR=1.6, 95%CI:1.2-2.3, P=0.006) was observed. When analyzing CHIP in genes related to myeloid malignancies, the association with non-CLL-type MBL was also significant (OR=1.6, 95%CI:1.1-2.3, P=0.012); however, the association was not statistically significant for genes related to lymphoid malignancies (OR=1.6, 95%CI:0.8-3.3, P=0.165). With a median follow-up of 5.4 years, 104 individuals developed incident hematologic malignancies (66 lymphoid and 38 myeloid malignancies). Non-CLL-type MBL (HR=3.5, 95%CI:1.9-6.5, P&lt;0.001) and CHIP (HR=3.2, 95%CI:2.1-5.1, P&lt;0.001) were each associated with increased risk of incident hematologic malignancies. Co-existence of both precursor conditions was associated with a substantially higher risk of incident hematologic malignancies (HR=10.3, 95%CI:4.0-26.2, P&lt;0.001) compared to individuals with neither precursor condition. Among individuals with non-CLL-like MBL, any CHIP was a borderline significant predictor for incident hematologic malignancy (HR=3.6, 95%CI:1.0-12.9, P=0.049). Compared to individuals with no precursor conditions, OS was not significantly different in those with non-CLL-type MBL-only (HR=1.1, 95%CI:0.8-1.5, P=0.40), those with CHIP-only (HR=1.2, 95%CI:0.99-1.4, P=0.06), or those with both CHIP and non-CLL-type MBL (HR=1.3, 95%CI:0.8-2.1, P=0.39). Conclusions: In the largest screening cohort to date evaluating the relationship of CHIP and non-CLL-type MBL, we found that non-CLL-type MBL and CHIP are associated with each other. Individuals with non-CLL-type MBL were more likely to have CHIP variants in DNMT3A, TET2, ASXL1, and ATM. Among individuals with non-CLL-type MBL, the presence of any CHIP was associated with increased risk of developing hematologic malignancy.

Abstract Background Mosaic chromosomal alterations (mCAs) are large-scale somatic gains, losses, or copy-neutral loss of heterozygosity (CNLOH) detectable by genotyping of peripheral blood DNA. They represent a form of clonal hematopoiesis and are observed in 0.5-5% of cancer-free individuals. The presence of any autosomal mCA has been associated with &gt;3-fold risk of hematological malignancies. In particular, mCAs occurring in regions related to lymphoid malignancies have an 11-fold increased risk of lymphoid malignancies and a 68.6-fold risk for chronic lymphocytic leukemia (CLL). Monoclonal B-cell lymphocytosis (MBL), the precursor state to CLL, is defined by &lt;5×10⁹/L clonal B cells in otherwise healthy individuals and is classified as low-count (&lt;0.5x109/L) or high-count (0.5-5x10⁹/L) based on clonal B-cell count. MBL is also associated with increased risk of lymphoid malignancy (beyond CLL), with 4.3-fold and 74-fold risk in individuals with low- and high-count MBL, respectively. We previously reported a significant enrichment of autosomal mCAs in MBL, demonstrating a 1.7-fold association in those with low-count MBL and a 50.5-fold association in those with high-count MBL. Whether mCAs independently predict lymphoid malignancy risk after accounting for MBL status is unknown. Here, we evaluated the impact of mCAs on risk of incident lymphoid malignancies in individuals with MBL and in individuals screened negative for MBL. Methods CLL-type MBL (CD5 positive) was identified using flow cytometry assay on peripheral blood. Participants were age ≥40, had no prior hematologic malignancy, and were enrolled through the Mayo Clinic Biobank or the Division of Hematology at Mayo Clinic, Rochester. Participants were followed for incident lymphoid malignancy, including CLL, with diagnoses confirmed by medical record review. mCAs with cell fraction &gt;1% were detected from array-based genotyping of whole blood DNA. Cox proportional hazards models, adjusted for age and sex, estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of developing an incident lymphoid malignancy in individuals with autosomal mCA versus those without an autosomal mCA. Results In 4,331 participants with available MBL and mCA status, the median age was 67 years, and 45% were male. Flow cytometry identified 3,231 individuals who screened negative for MBL, 754 individuals with low-count MBL, and 346 individuals with high-count MBL. Autosomal mCAs were present in 6.5% of individuals without MBL, 7.6% with low-count MBL, and 71.1% with high-count MBL. Over a median follow-up of 6.9 years, 237 individuals developed an incident lymphoid malignancy. The most common types were CLL, multiple myeloma, and diffuse large B-cell lymphoma. Ignoring MBL status, the presence of an autosomal mCA was associated with increased risk of lymphoid malignancy (HR = 2.65; 95% CI: 1.45–4.86; P = 0.002), replicating previous results. However, after excluding individuals with MBL, this association attenuated; those with mCA alone did not have a significantly elevated risk (HR = 1.60; 95% CI: 0.57-4.52; P = 0.38) compared to individuals without MBL or mCA. We next examined the effect of mCAs among individuals with MBL. In those with low-count MBL, the most frequent mCA events were 13q loss (2.1%), 12 gain (1.9%), and 4q CNLOH (1.2%), and individuals with an mCA had a borderline significant risk of developing a lymphoid malignancy (HR = 2.78; 95% CI: 1.01–7.67; P = 0.049) compared to those without an mCA. Similarly, in those with high-count MBL, the most frequent mCA events were 13q loss/CNLOH (31.2%), 12 gain (13.0%), and 11q loss (4.9%), and the presence of an mCA conferred an increased risk compared to those without mCA (HR = 1.51; 95% CI: 1.09-2.08; P = 0.012). Conclusions Autosomal mCAs were more frequent in individuals with high-count MBL compared to those with low-count or no MBL. mCAs showed limited predictive value for lymphoid malignancy among individuals without MBL. In contrast, in individuals with low-count MBL, autosomal mCAs emerged as a potential biomarker for identifying those at risk of developing a lymphoid malignancy. In high-count MBL, mCAs were also a biomarker, but were driven by known chromosomal abnormalities identified through clinical testing. These findings suggest that the utility of mCAs as a predictive marker for lymphoid malignancy is contingent on the presence of MBL and may inform risk stratification and surveillance strategies in this population.

e15003 Background: Antibody-drug conjugates (ADCs) have shown substantial promise as therapies for metastatic breast cancer (mBC). However, direct comparisons of different ADC-based regimens are limited. We assessed survival outcomes in mBC patients treated with ADCs. Methods: Randomized controlled trials (RCTs) published before October 2024 were searched in Medline, Embase, ClinicalTrials.gov, and Cochrane Library. Progression-free survival (PFS) and overall surcvival (OS) outcomes were extracted from the most updated publications. Participants were stratified based on molecular subtypes, hormone receptor (HR) status, duration of cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) treatment, and sensitivity to endocrine therapy (ET). Bayesian frameworks were deployed, presenting the synthesized outcomes of indirect comparisons using the surface under the cumulative ranking curve (SUCRA), hazard ratio (HR), and 95% credible interval (Crl). This study was prospectively registered on the International Platform of Registered Systemic Reviews and Meta-analysis Protocols (INPLASY) (INPLASY2024110021). Results: A total of 6449 patients from 12 RCTs of ADCs ado-trastuzumab emtansine (T-DM1), sacituzumab govitecan (SG), trastuzumab deruxtecan (T-DXd), and datopotamab deruxtecan (Dato-DXd) were included in the analysis. Compared to chemotherapy, T-DXd significantly improved PFS (HR 0.35, 95% Crl 0.15-0.84) and OS (HR 0.56, 95% Crl 0.32-1.0). SG also significantly extended OS (HR 0.65, 95% Crl 0.43-0.97) but not PFS. In HER2+ mBC, pooled analyses revealed T-DXd was the most effective treatment in terms of PFS, with a SUCRA of 94.2%, followed by T-DM1 (58.9%), and chemotherapy with HER2-directed therapy (34.2%). Synthesized outcomes of OS mirrored the PFS outcomes. In HR+/HER2- mBC (some of which was HER2-low), Dato-DXd (76.1%) showed slightly superior efficacy over SG (67.4%) for PFS, while SG (85.1%) was advantageous over Dato-DXd (49.1%) in terms of OS. Among patients with HR+/HER2+ mBC, T-DXd (80.0%), SG (55.5%), and chemotherapy with HER2-directed therapy (53.1%) were the most effective therapies for prolonging PFS. Regarding OS, SG (70.3%) and T-DM1 (60.3%) were the most effective, with comparable efficacy observed between chemotherapy with HER2-directed therapy (52.1%) and T-DXd (52.0%). In HR-/HER2+ mBC, T-DXd (78.1%), SG (56.1%), and T-DM1 (51.5%) significantly prolonged PFS, while SG (69.4%) had the most substantial benefit for OS, followed by T-DXd (62.8%) and chemotherapy with HER2-directed therapy (57.6%). Dato-DXd showed an advantage over SG in mBC patients received CDK4/6i for > 12 months. Conclusions: This network meta-analysis showed prominent survival benefits with ADC-containing regimens for mBC. Our results provide valuable insights into personalized treatment strategies for mBC patients.

Objectives: To evaluate the clinical heterogeneity of sarcomas by examining associations between histological subtypes, metastatic patterns, treatment modalities, and survival outcomes. Methods: We analyzed data from 97,062 adult patients diagnosed with sarcoma between 2000 and 2020, using the Surveillance, Epidemiology, and End Results (SEER) database. Fourteen histological subtypes were included. Propensity score matching (PSM) was employed to adjust for baseline differences, and Cox proportional hazards models were used to identify prognostic variables. Results: The most prevalent subtypes were sarcoma not otherwise specified (31.9%), leiomyosarcoma (17.1%), and liposarcoma (13.9%). Metastatic patterns differed significantly by subtype; liver metastases were most common in sarcomas with small blue round cell (SBRC) features (8.9%) and stromal sarcoma (6.1%), while lung metastases were frequently observed in Ewing sarcoma (10.0%) and rhabdomyosarcoma (9.7%). Median overall survival (mOS) varied widely, ranging from 234 months in chondrosarcoma to 16–20 months in rhabdomyosarcoma and SBRC sarcoma. Overall, patients with primary sarcoma had significantly better survival than those with treatment-related disease (119.0 vs. 45.0 months, p < 0.0001), with this trend consistent across most subtypes. Treatment responses were subtype- and size-dependent. For instance, surgery plus radiotherapy improved outcomes in giant cell sarcoma regardless of tumor size, whereas chemotherapy provided benefit only in tumors larger than 5 cm. Combined surgery and radiotherapy offered additional survival benefit in select subtypes, including chordoma, leiomyosarcoma (>5 cm), and synovial sarcoma (<5 cm). Conclusions: Sarcomas exhibit substantial clinical and prognostic heterogeneity across histological subtypes. These findings underscore the importance of subtype-specific, individualized treatment strategies in optimizing patient outcomes.