Survival Analysis Models Research Articles

Neck dissection of cN0 maxillary oral squamous cell carcinoma: A study based on SEER database

ObjectiveFor patients with clinical nodal-negative (cN0) maxillary oral squamous cell carcinoma (MOSCC), neck dissection (ND) and clinical observation are the main two management strategies for the neck. However, the indications corresponding to these two options remain controversial. This study aimed to elucidate the clinical factors affecting ND treatment and to identify clinical characteristics of the population that may benefit from ND based on a retrospective analysis of cN0 MOSCC patient data from the Surveillance, Epidemiology, and End Results (SEER) database. Methods8846 MOSCC patients were identified in the SEER database from 2000 to 2020. The Kaplan-Meier method was utilized to examine overall survival (OS) and disease-specific survival (DSS), while the hazard ratio (HR) was estimated using the stepwise multivariate Cox regression model. Furthermore, multi-subgroup analyses of DSS and OS were performed to compare ND and No ND. ResultsWe included 2,512 cN0 MOSCC patients. Basic survival analysis and Cox regression modeling showed that ND was an independent prognostic factor that promoted DSS and OS. Additional subgroup analyses revealed that the primary site and T-stage might influence the efficacy of ND modality. Moreover, patients with T3/T4 stage of upper gingival squamous cell carcinoma (UGSCC) (DSS p = 0.009, OS p = 0.004), hard palate squamous cell carcinoma (HPSCC) (DSS p = 0.001, OS p < 0.001), and soft palate squamous cell carcinoma (SPSCC) (p = 0.029) showed a better survival benefit with ND in OS and DSS. Nonetheless, no differences were observed in OS and DSS between ND and No ND at the T1/T2 stage of the abovementioned primary tumor sites. Additionally, the DSS outcomes for T1/T2 stage upper lip squamous cell carcinoma (ULSCC) patients were significantly worse in the ND group than in the No ND group (p = 0.018). However, no significant differences were noted in OS (p = 0.140) as well as OS (p = 0.248) and DSS (p = 0.627) for T1/T2 and T3/T4 patients, respectively. ConclusionActive surveillance might be a feasible strategy for managing all T-staged ULSCC as well as early-stage (T1/T2) UGSCC, SPSCC, and HPSCC, provided regular and meticulous follow-up is performed. Hence, concurrent ND is recommended for patients with intermediate to advanced (T3/T4) stage UGSCC, SPSCC, and HPSCC.

Associations between transfusion reactions and thromboembolism development in blood-transfused patients: A retrospective cohort study.

Blood transfusion (BT) may be associated with an increased risk of thromboembolism. The associations between transfusion reactions (TRs) during BTs and potential risk factors for the development of thromboembolism in patients underwent blood transfusion have not been analyzed. Therefore, this study aimed to compare risk factors associated with the development of venous thromboembolism (VTE) or pulmonary embolism (PE) between patients underwent blood transfusion with and without TRs. The retrospective study was conducted between April 1, 2017, and March 31, 2020, at a medical center in Taiwan. Blood-transfused patients were grouped into two cohorts as follows: those who experienced TRs and those who did not experience TRs. Both cohorts were subjected to follow-up until March 31, 2021. The endpoints for both groups were the occurrence of VTE or PE or the date of March 31, 2021. To investigate between-cohort risk differences, a Kaplan-Meier survival analysis and multiple Cox proportional hazard model was used. A total of 10,759 patients underwent 59,385 transfusion procedures, with 703 patients in the TR group, and 10,056 patients in the non-TR group. The risk of VTE or PE was twice as high in the TR group than in the non-TR group (adjusted hazard ratio 2.53, 95% confidence interval 1.49-4.29, p = .001). Meanwhile, age, female sex, transfusion frequency increment, and being nondiabetic was associated with an increased risk of developing thromboembolism. TRs are associated with increased long-term thromboembolism risk in patients underwent blood transfusion. It is imperative for clinicians to acknowledge this and maintain rigorous follow-up.

Evaluating the Efficacy of Adjuvant Radiotherapy in the Management of Advanced Oral Cancer Cases.

Because of its high rates of morbidity and death, especially in its late stages, oral cancer poses a serious threat to world health. Even with improvements in surgical and chemotherapeutic techniques, advanced oral cancer is still difficult to treat and frequently has unfavorable results. Information on demographics, tumor features, treatment options, and results were gathered from medical records. Patients were categorized according to whether they underwent surgery alone or adjuvant radiation treatment after initial surgical resection. For the survival analysis, Kaplan-Meier curves and Cox proportional hazards models were employed. There were 150 patients in all, 75 in each group, who took part in the trial. Comparing adjuvant radiation to surgery alone resulted in considerably better overall survival (P < 0.001) and disease-free survival (P < 0.001). However, problems connected to the adjuvant radiation group affected a portion of the patient population. In conclusion, patients with advanced oral cancer can improve their overall and disease-free survival with adjuvant radiation, a successful therapeutic option. To maximize results, nevertheless, cautious patient selection and effective management of treatment-related problems are crucial. To improve treatment algorithms and investigate cutting-edge therapeutic techniques for this difficult condition, further research is necessary.

A randomized control trial to compare mortality in recipients of leucoreduced and non-leucoreduced whole blood transfusion in patients with cancer in Uganda

BackgroundMortality benefit of transfusion with leucoreduced whole blood has not been demonstrated in the sub-Saharan Africa (SSA). We compared mortality in patients with cancer transfused with leucoreduced and non-leucoreduced whole blood in a SSA setting.MethodsAn open-label randomized controlled trial was conducted at the Uganda Cancer Institute where participants were randomized in a 1:1 ratio into the leucoreduced and non-leucoreduced whole blood transfusion arms. Leucocyte filtration of whole blood was performed within 72 h of blood collection. Patients aged ≥ 15 years who were prescribed blood transfusion by the primary physicians were eligible for study enrolment. Mortality difference was analyzed using intention-to-treat survival analysis and cox proportional hazard model was used to analyze factors associated with mortality.ResultsThere were 137 participants randomized to the leucoreduced and 140 to the non-leucoreduced arms. Baseline characteristics were similar between the two arms. The median number of blood transfusions received was 1 (IQR, 1–3) unit and 2 (IQR, 1–3) units in the leucoreduced and non-leucoreduced arms respectively, p = 0.07. The 30-day mortality rate in the leucoreduced arm was 4.6% (95% CI, 2.1–10) and was 6.2% (95% CI, 3.2–12.1) in the non-leucoreduced arm (p = 0.57), representing an absolute effect size of only 1.6%. Increasing age (HR = 0.92, 95% CI, 0.86–0.98, p = 0.02) and Eastern Co-operative Oncology Group (ECOG) performance score of 1 (HR = 0.03, 95% CI, 0.00–0.31, p < 0.01) were associated with reduced 30-day mortality.ConclusionsThe study failed to demonstrate mortality difference between cancer patients transfused with leucoreduced and non-leucoreduced whole blood. Although this study does not support nor refute universal leucoreduction to reduce mortality in patients with cancer in SSA, it demonstrates the feasibility of doing transfusion RCTs in Uganda, where a multi-center trial with an appropriate sample size is needed.Trial registrationPan African Clinical Trial Registry, https://pactr.samrc.ac.za/ (PACTR202302787440132). Registered on 06/02/2023.

Prognostic Impact of Body Mass Index in Atrial Fibrillation.

Background/Objectives: Contradictory results have been reported regarding the influence of obesity on the prognosis of atrial fibrillation (AF). The present study aimed to explore the potential association of body mass index (BMI) with the clinical outcomes of hospitalized patients with AF. Methods: In this retrospective, post hoc analysis of the MISOAC-AF randomized trial, 1113 AF patients were included and stratified as the following: underweight (BMI < 18 kg/m2), normal weight (BMI 18-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2), and obese (BMI ≥ 30 kg/m2). The primary outcome was all-cause mortality; the secondary composite outcome was any hospitalization related to AF, heart failure (HF), or stroke. Cox regression analysis, survival analysis, and spline curve models were utilized. Results: Of the patients (median age: 76 years (IQR: 13), male: 54.6%), the majority were overweight (41.4%), followed by obese (33%), normal weight (24%), and underweight (1.6%). During a median 31-month follow-up, 436 (39.2%) patients died and 657 (59%) were hospitalized due to AF, HF, or stroke. Underweight, overweight, and obesity groups were significantly associated with an increased risk of all-cause mortality (p-values 0.02, 0.001, and <0.001, respectively), while overweight and obesity were significantly associated with the composite endpoint (p-values 0.01, <0.001, respectively) compared to normal weight. The spline curve analyses yielded that BMIs > 26.3 and > 25 were incrementally associated with all-cause mortality and the composite endpoint, respectively. A J-shaped relationship between BMI and AF prognosis was deduced. Conclusions: In conclusion, in recently hospitalized AF patients, BMI values outside the normal range were independently associated with poorer prognosis; therefore, it is essential that AF patients maintain a normal weight.

Disease-free survival after pancreatectomy for pancreatic neuroendocrine tumors: A 17-year single-center experience of 223 patients

BackgroundMetastasis or recurrence of pancreatic neuroendocrine tumors (pNETs) after pancreatectomy is an important source of postsurgical morbidity. This study aimed to define disease-free survival (DFS) in this population. MethodsPatients who underwent pancreatectomy for pNETs between January 2005 and January 2022 were included. Clinicopathologic and survival data were collected, and the primary endpoint was DFS. Kaplan-Meier survival analysis and Cox proportional hazards regression modeling were performed. ResultsOf the 223 patients, 144 (65%) distal/subtotal/partial pancreatectomies, 71 (32%) pancreaticoduodenectomies, 6 (3%) total pancreatectomies, and 2 (1%) enucleations were performed. Of the 223 patients, 45 (20%) experienced disease recurrence or metastasis after index pancreatectomy during the 17 years of the study. Nonfunctional pNETs (162 [73%]) were more common than hormonally functional subtypes. The 2- and 5-year DFSs were 82% and 76%, respectively. Kaplan-Meier analysis demonstrated that N1 node positive disease, size of ≥ 4 cm, lymphovascular invasion, perineural invasion, Ki-67 of ≥ 20%, and nonfunctional pNETs are significantly associated with a lower DFS (P < .05). Univariate Cox analysis identified the following predictors to be significantly associated with poorer DFS: larger tumor size (hazard ratio [HR], 1.16; 95% CI, 1.04–1.28), Ki-67 index of ≥ 20% (HR, 4.93; 95% CI, 2.00–11.44), perineural invasion (HR, 3.23; 95% CI, 1.40–7.89), open surgery (HR, 3.34; 95% CI, 1.03–1.33), node-positive disease (HR, 5.27; 95% CI, 2.28–13.26), and increased body mass index (HR, 1.10; 95% CI, 1.03–1.17) (P < .05). ConclusionOf note, 1 in 5 patients who underwent resection developed recurrence or metastasis after pancreatectomy. Prognostic predictors of DFS in pNETs could help optimize treatment and enhance follow-up protocols to improve quality and reduce morbidity.

Neoadjuvant chemotherapy as an indication to preserve nipple areolar complex in advanced breast cancer.

e12655 Background: Nipple areolar skin sparing mastectomy (NASSM) has similar oncologic and surgical safety compared to skin sparing mastectomy (SSM) and conventional mastectomy. It provides a superior cosmetic outcome, patient satisfaction and quality of life. With the increasing rate of pathological response rate with neoadjuvant chemotherapy (NAT), nipple preservation can be achieved. The aim of our study is to evaluate whether NASSM is an appropriate surgical procedure for patients in whom there is radiological evidence of extension or involvement of nipple areolar complex (NAC) prior to NAT. Methods: Patients with advanced breast cancer received neoadjuvant chemotherapy and NASSM or SSM between June 2006 and December 2021 at Asan Medical Center were retrospectively reviewed. We excluded patients with metastatic breast cancer on presentation, bilateral cancer and inflammatory breast cancer. Kaplan-Meier survival analysis and Cox proportional hazard models were applied to determine clinicopathological and radiological factors to determine NAC preservation. Our primary objective to assess tumor cells persistence in the NAC after radiological complete response or resolution of extension to NAC. Results: Total of 1,105 patients included. 71.7% of patients underwent NASSM and 17.2% SSM as a final operation. 144 patients (13%) had a change in the pre- NAT type of surgery decision. 83(7.5%) patients had nipple involvement on final pathology. Out of 312 patients who underwent SSM, only 76 patients had nipple involvement on final pathology When comparing patients who had nipple involvement to those who didn’t on final pathology, clinical T &amp; N stage, histologic &amp; nuclear grade, breast cancer subtype, presence of multifocality/multicentric disease on MRI pre or post NAT, distance of mass to NAC and mass size pre and post NAT, the presence of non mass extension to NAC post NAT, NAC thickening on any image pre and post NAT and presentation symptoms of nipple retraction and skin changes were statistically significant. A multivariate regression analysis was performed to compare all the above factors and showed that breast cancer subtype, tumor nipple distance on MRI pre NAT, nipple areolar thickening on MRI pre NAT, clinical response and nipple retraction on MMG post NAT were statistically significant and indicators of nipple involvement on final pathology. Only 8 patients developed NAC recurrence in the NASSM group. Conclusions: NASSM is a safe procedure in patients who had tumor extension to NAC prior to NAT and showed improvement post NAT as evident on MRI. Further prospective studies are needed to establish and criteria to preserve NAC in this subgroup of patients.

Exploring the nexus between past financial performance and voluntary GRI adoption: The role of environmental certification

Numerous firms have adopted the Global Reporting Initiative (GRI) standards to enhance sustainability. Using panel data from 2008 to 2020, we employ logit, probit, complementary log-log, and Cox survival analysis models to explore the factors which affect the adoption of the GRI standards in the context of voluntary disclosure in China. Our findings indicate that past financial performance significantly influences decisions on GRI adoption. Environmental certification moderates the effect of financial performance on GRI adoption. Notably, the cross-sectional test reveals that financial performance plays a stronger role in GRI adoption among companies with low information transparency compared to those with high information transparency.

Prognostic insights, immune infiltration, and therapeutic response: Cytoplasmic poly(A) tail regulators in hepatocellular carcinoma

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA-seq data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF) and principal component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

Circadian rhythm dysfunction and psychopathology in the offspring of parents with bipolar disorder: a high-risk study in the Chinese population

BackgroundUnderstanding the evolution of circadian rhythm dysfunction and psychopathology in the high-risk population has important implications for the prevention of bipolar disorder. Nevertheless, some of the previous studies on the...

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis.

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.

Nucleoporin 93 Regulates Cancer Cell Growth and Stemness in Bladder Cancer via Wnt/β-Catenin Signaling.

Bladder cancer (BLCA) is a prevalent cancer type with an unmet need for new therapeutic strategies. Nucleoporin 93 (Nup93) is implicated in the pathophysiology of several cancers, but its relationship with bladder cancer remains unclear. Nup93 expression was analyzed in TCGA datasets and 88 BLCA patient samples. Survival analysis and Cox regression models evaluated the association between Nup93 levels and patient prognosis. BLCA cells were used to investigate the effects of Nup93 overexpression or knockdown on cell growth, invasion, stemness (sphere formation and ALDH2 + cancer stem cell marker), and Wnt/β-catenin signaling in vitro. The Wnt activator BML-284 was used to confirm the involvement of Wnt/β-catenin signaling pathway. A xenograft mouse model validated the in vitro findings. Nup93 was highly expressed in BLCA tissues and cell lines, and high Nup93 expression correlated with poor prognosis in BLCA patients. Nup93 silencing inhibited BLCA cell proliferation, Wnt/β-catenin activation, and cancer cell stemness. Conversely, Nup93 overexpression promoted these effects. BML-284 partially rescued the reduction in cell growth and stemness markers caused by Nup93 knockdown. Nup93 knockdown also suppressed the tumor formation of BLCA cells in vivo. Nup93 regulates BLCA cell growth and stemness via the Wnt/β-catenin pathway, suggesting its potential as a prognostic marker and therapeutic target in BLCA.

Rank-based sequential feature selection for high-dimensional accelerated failure time models with main and interaction effects

High-dimensional accelerated failure time (AFT) models are commonly used regression models in survival analysis. Feature selection problem in high-dimensional AFT models is addressed, considering scenarios involving solely main effects or encompassing both main and interaction effects. A rank-based sequential feature selection (RankSFS) method is proposed, the selection consistency is established and illustrated by comparing it with existing methods through extensive numerical simulations. The results show that RankSFS achieves a higher Positive Discovery Rate (PDR) and lower False Discovery Rate (FDR). Additionally, RankSFS is applied to analyze the data on Breast Cancer Relapse. With a remarkable short computational time, RankSFS successfully identifies two crucial genes.

WhARIO: whole-slide-image-based survival analysis for patients treated with immunotherapy.

Immune checkpoint inhibitors (ICIs) are now one of the standards of care for patients with lung cancer and have greatly improved both progression-free and overall survival, although of the patients respond to the treatment, and some face acute adverse events. Although a few predictive biomarkers have integrated the clinical workflow, they require additional modalities on top of whole-slide images and lack efficiency or robustness. In this work, we propose a biomarker of immunotherapy outcome derived solely from the analysis of histology slides. We develop a three-step framework, combining contrastive learning and nonparametric clustering to distinguish tissue patterns within the slides, before exploiting the adjacencies of previously defined regions to derive features and train a proportional hazards model for survival analysis. We test our approach on an in-house dataset of 193 patients from 5 medical centers and compare it with the gold standard tumor proportion score (TPS) biomarker. On a fivefold cross-validation (CV) of the entire dataset, the whole-slide image-based survival analysis for patients treated with immunotherapy (WhARIO) features are able to separate a low- and a high-risk group of patients with a hazard ratio (HR) of 2.29 ( to 3.56), whereas the TPS 1% reference threshold only reaches a HR of 1.81 ( to 2.69). Combining the two yields a higher HR of 2.60 ( to 3.94). Additional experiments on the same dataset, where one out of five centers is excluded from the CV and used as a test set, confirm these trends. Our uniquely designed WhARIO features are an efficient predictor of survival for lung cancer patients who received ICI treatment. We achieve similar performance to the current gold standard biomarker, without the need to access other imaging modalities, and show that both can be used together to reach even better results.

Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features

BackgroundSemiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients’ survival analysis.MethodsTraining (n = 411) and testing (n = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic.ResultsAlthough the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis.ConclusionsThe Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival.Trial registrationClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/, date of registration: 30th June 2017.

Improved nonparametric survival prediction using CoxPH, Random Survival Forest & DeepHit Neural Network

In recent times, time-to-event data such as time to failure or death is routinely collected alongside high-throughput covariates. These high-dimensional bioinformatics data often challenge classical survival models, which are either infeasible to fit or produce low prediction accuracy due to overfitting. To address this issue, the focus has shifted towards introducing a novel approaches for feature selection and survival prediction. In this article, we propose a new hybrid feature selection approach that handles high-dimensional bioinformatics datasets for improved survival prediction. This study explores the efficacy of four distinct variable selection techniques: LASSO, RSF-vs, SCAD, and CoxBoost, in the context of non-parametric biomedical survival prediction. Leveraging these methods, we conducted comprehensive variable selection processes. Subsequently, survival analysis models—specifically CoxPH, RSF, and DeepHit NN—were employed to construct predictive models based on the selected variables. Furthermore, we introduce a novel approach wherein only variables consistently selected by a majority of the aforementioned feature selection techniques are considered. This innovative strategy, referred to as the proposed method, aims to enhance the reliability and robustness of variable selection, subsequently improving the predictive performance of the survival analysis models. To evaluate the effectiveness of the proposed method, we compare the performance of the proposed approach with the existing LASSO, RSF-vs, SCAD, and CoxBoost techniques using various performance metrics including integrated brier score (IBS), concordance index (C-Index) and integrated absolute error (IAE) for numerous high-dimensional survival datasets. The real data applications reveal that the proposed method outperforms the competing methods in terms of survival prediction accuracy.

Abstract PS01-06: The relationship between margin status of &amp;lt;2mm and local recurrence in DCIS patients

Abstract Background: There has been controversial evidence regarding adequate margin in breast conserving surgery (BCS) for ductal carcinoma in situ (DCIS). However, the consensus is a surgical margin distance of 2 mm. Moreover, recent recommendations advised on ‘’clinical judgement’’ approach to re-excision in cases of margin distance &amp;lt; 2mm. The ongoing controversy in DCIS margin compared to invasive cancer margin is due to the differences in post operative management. This is important as margin status is one of the modifiable risk factor for local regional recurrence in DCIS. In our study we evaluated margin distance in patient diagnosed with DCIS who underwent BCS on local recurrence Methods: Patients who underwent breast conserving surgery between February 2000 and December 2018 at Asan Medical Center were retrospectively reviewed. Patients with involved resection margins were excluded. Kaplan-Meier survival analysis and Cox proportional hazard models were applied to determine the relationship between negative margin width and local recurrence. Results: A total of 1,858 patients were included in the study. Almost half of the patients had a tumor size of 1cm or smaller (n=876, 47.1%). Only 98 (5.3%) patients did not undergo radiation therapy. A negative margin width of &amp;lt; 1mm, &amp;lt; 2mm, &amp;lt; 5mm were all not associated with local recurrence (log-rank test p-value 0.1, 0.1, 0.078, respectively). For patients who underwent radiation therapy, a negative margin of any width was not related to local recurrence. Whereas, for patients who did not undergo radiation therapy, those with margins ≤2mm were significantly more likely to develop local recurrence than those with margins &amp;lt; 2mm (10-yr local recurrence rate, 16.4% vs 5.5%, respectively; hazard ratio, 5.709; 95% CI, 1.106-29.46, p=0.038). Conclusion: A negative margin is not related to local recurrence in DCIS patients who undergo breast conserving surgery with radiation therapy. Routine additional surgery for wider negative margin may only be needed for patients who do not undergo radiation therapy. Citation Format: Sarah Al Safi, Tae-Kyung Yoo, Sae Byul Lee, Jisun Kim, Il-Yong Chung, Hee Jeong Kim, Beom Seok Ko, Jong Won Lee, Byung Ho Son, Hee Jin Lee, Gyungyub Gong. The relationship between margin status of &amp;lt;2mm and local recurrence in DCIS patients [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS01-06.

Abstract PO4-05-11: Effects of body mass index on the treatment outcome of patients with metastatic breast cancer in the real world

Abstract Purpose: Metastatic/recurrent breast cancer has a relatively long survival compared to other cancers and depending on the biologic subtype, the treatment outcome is different. In general, obesity or overweight is associated with poor prognosis of breast cancer, but the relationship between body mass index (BMI) and prognosis in metastatic cases is not clear. The aim of this study is investigating the effect of BMI on survival outcome through long-term follow-up in single institution, retrospectively. Method: This study included the patients with metastatic/recurrent breast cancer who has been diagnosed from January 2000 to December 2022 in an institution. BMI was calculated based on weight at diagnosis of metastatic disease, divided into 4 groups according to Asian-Pacific classification, and clinical characteristics including biologic subtype and overall survival (OS) were retrospectively reviewed. The statistical analysis was performed using Kaplan-Meier survival analysis and Cox proportional hazard model. Result: A total of 679 patients were enrolled. Median age was 51 years-old (25~89), 672 patients (99.0%) were female and 425 patients (62.6%) showed pre-menopausal status. The frequencies of HR+, HER2, and TNBC subtype were 335 (50.7%), 191 (28.9%), and 135 (20.4%), respectively and the BMI classification was 33 (5.5%), 251 (41.6%), 124 (20.5%), 196 (32.4%) for underweight, normal, overweight, and obesity, respectively. During a median follow-up of 33.8 months, the median OS in each of the HR+, HER2+, and TNBC subgroups was 54.9 (95% CI 38.7-71.1), 62.8 (95% CI 47.8-77.8), and 20.8 months (95% CI 12.0-29.7). In univariate analysis, there was no statistically significant difference in OS according to BMI in whole patients, however, in the HER2-positive group, the underweight BMI group showed poor OS (p=0.045). In multivariate analysis, the factors affecting OS were age (HR 0.59, 95% CI 0.41-0.87, p=0.008), poor ECOG PS (HR 8.35, 95% CI 2.54-27.49, p&amp;lt; 0.001), TNBC subtype (HR 2.14, 95% CI 1.56-2.94, p&amp;lt; 0.001), visceral metastasis (HR 2.13, 95% CI 1.63-2.79, p&amp;lt; 0.001), 5% or more weight loss during treatment (HR 1.46, 95% CI 1.09-1.97, p=0.012) and obesity BMI group (HR 0.69, 95% CI 0.51-0.94, p=0.019). Conclusion: In the case of patients with metastatic/recurrent breast cancer, there is concern about an increase in body weight, a known risk factor for breast cancer, while receiving palliative aim treatment. For the past 20 years, the mainstay of treatment for metastatic/recurrent breast cancer has been cytotoxic chemotherapy or anti-HER2 agents, and in this case, the higher BMI group patients showed better treatment outcomes compared with normal BMI patients. Citation Format: Kyoung Eun Lee, Ahrong Ham, Sewon Lee, Jungmin Jo, Soo Ji Hong, Ji Eun Lee, Haena Lee, Sungchan Gwark, Jeongshin An, Hyun-Goo Kim, Jun Woo Lee, Joohyun Woo, Woosung Lim, Byung-In Moon, Sei Hyun Ahn, Hye Ah Lee. Effects of body mass index on the treatment outcome of patients with metastatic breast cancer in the real world [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-05-11.

Efficacy and safety of PD-1/PD-L1 inhibitors in elderly patients with advanced non-small cell lung cancer.

This study aimed to investigate the efficacy and safety of PD-1/PD-L1 inhibitors in treatment of elderly patients with advanced non-small cell lung cancer (NSCLC). Patients with advanced NSCLC ≥70 years old who received PD-1/PD-L1 inhibitors in our hospital were retrospectively analyzed. According to age, the patient were stratified as follows: 70-75 years old, 76-80 years old, and >80 years old. Kaplan-Meier method was used for survival analysis, and univariate and multivariate Cox proportional hazards regression models were used to analyze the correlation between different clinical characteristics and survival. A total of 58 elderly patients with advanced non-small cell cancer were enrolled in this study. Patients aged 70-75, 76-80, and >80 years old were 32, 19, and 7, respectively. For the all, median OS was 17.0months, and PFS was 7.0months. PFS and OS did not differ according to age (P = 0.396, 0.054, respectively). Univariate analysis showed that PS of 0-1, stage III, first-line therapy and irAEs were associated with longer PFS, and PS of 0-1, stage III, and first-line therapy were associated with longer OS. Multivariate analysis showed that patients with stage III had longer PFS. PFS and OS of patients with PS ≥ 2 were significantly shorter than those of patients with PS of 0-1. In the present real-world retrospective cohort, PD-1/PD-L1 inhibitors are effective and well tolerated in elderly patients with advanced NSCLC. Immunotherapy should be actively used as early as possible in older patients advanced NSCLC.

Characteristics and significance of programmed cell death-related gene expression signature in skin cutaneous melanoma.

Programmed cell death (PCD) pathways play crucial roles in the pathogenesis of skin cutaneous melanoma (SKCM). Understanding their prognostic significance and clinical implications is imperative for the development of personalized treatment strategies. A total of 1466 PCD-related genes were analyzed using data from The Cancer Genome Atlas (TCGA)-SKCM cohort (n=353). Prognostic cell death index (CDI) was established and validated through survival analysis and predictive modeling. Functional enrichment, protein-protein interaction (PPI), consensus clustering, and tumor microenvironment assessment and drug sensitivity analysis were performed to elucidate the biological and clinical relevance of CDI. CDI effectively stratified SKCM patients into high and low-risk groups, demonstrating significant differences in survival outcomes. It exhibited predictive value for survival at 1, 3, and 5 years. The concordance index (C-index) was 0.794 in the training set, and 0.792 and 0.821 in the internal and external validation sets, respectively. The corresponding area under curve (AUC) was all above 0.75 in these data sets. Functional enrichment analysis revealed significant associations with immune response and inflammatory processes. PPI analysis identified key molecular modules associated with apoptosis and chemokine signaling. Consensus clustering unveiled three discernible subtypes demonstrating notable disparities in survival outcomes based on CDI expression profiles. Assessment of the tumor microenvironment highlighted correlations with immune cell infiltration such as M1 macrophages and T cells. Drug sensitivity analysis indicated tight correlations between CDI levels and response to immunotherapy. Our comprehensive analysis establishes the prognostic significance of PCD-related genes in SKCM. CDI emerges as a promising prognostic biomarker, offering insights into tumor biology and potential implications for personalized treatment strategies. Further validation and clinical integration of CDI are warranted to improve SKCM management and patient outcomes.