Number Of Positive Nodes Research Articles

Impact of neoadjuvant chemotherapy on breast cancer-related lymphedema after axillary lymph node dissection: a retrospective cohort study.

We aimed to evaluate whether neoadjuvant chemotherapy (NAC) could be a risk factor for breast cancer-related lymphedema (BCRL) associated with axillary lymph node dissection (ALND). A total of 596 patients with cT0-4N0-3M0 breast cancer who underwent ALND and chemotherapy were retrospectively analyzed between March 2012 and March 2022. NAC was administered in 188 patients (31.5%), while up-front surgery in 408 (68.5%). Univariate and multivariable Cox regression analyses were performed to determine whether NAC was an independent risk factor for BCRL. With propensity score matching (PSM), the NAC group and up-front surgery group were matched 1:1 by age, body mass index (BMI), molecular subtypes, type of breast surgery, and the number of positive lymph nodes. Kaplan-Meier survival analyses were performed for BCRL between groups before and after PSM. Subgroup analyses were conducted to explore whether NAC differed for BCRL occurrence in people with different characteristics. At a median follow-up of 36.3months, 130 patients (21.8%) experienced BCRL [NAC, 50/188 (26.60%) vs. up-front surgery, 80/408 (19.61%); P = 0.030]. Multivariable analysis identified that NAC [hazard ratio, 1.503; 95% CI (1.03, 2.19); P = 0.033] was an independent risk factor for BCRL. In addition, the hormone receptor-negative/human epidermal growth factor receptor 2-negative (HR-/HER2-) subtype, breast-conserving surgery (BCS), and increased positive lymph nodes significantly increased BCRL risk. After PSM, NAC remained a risk factor for BCRL [hazard ratio, 1.896; 95% CI (1.18, 3.04); P = 0.007]. Subgroup analyses showed that NAC had a consistent BCRL risk in most clinical subgroups. NAC receipt has a statistically significant increase in BCRL risk in patients with ALND. These patients should be closely monitored and may benefit from early BCRL intervention.

Application of parametric survival analysis to women patients with breast cancer at Jimma University Medical Center

Public health systems in both industrialized and undeveloped countries continue to struggle with the worldwide problem of breast cancer. In sub-Saharan African countries, notably Ethiopia, it is the form of cancer that strikes women the most commonly. Despite the extreme difficulties, the causes of mortality in Ethiopia have not yet been identified. In addition, little study has been done in this area. Therefore, the major objective of this analysis was to pinpoint the factors that were most responsible for the decreased life expectancy of breast cancer patients at the University of Jimma Medical Center. 552 women who had been treated for breast cancer at Jimma University Medical Center between October 2018 and December 2022 were included in this study, which used a retrospective cohort study design and five-year follow-up data. The most frequent and widely used test for comparing the probability of survival curves between several categorical independent variables was the log-rank test. Next, semi-parametric methods for multivariable analysis using the Cox proportional hazards model were used. Furthermore, a parametric strategy that includes fully parametric survival models better achieves the goal of the analysis. Among covariate, age of patient (ϕ = 254.06; 95% CI (3.95, 7.13), P-value = 0.000), patient live in urban (ϕ = 0.84; 95% CI (-0.35,-0.00), P-value = 0.047), preexisting comorbidity (ϕ = 2.46; 95% CI (0.39, 1.41), P-value = 0.001), overweight women cancer patient (ϕ = 0.05; 95% CI(-4.41,-1.57), P-value = 0.000, positive Axillary Node status cancer patient (ϕ = 0.04; 95% CI(-4.45,-1.88), P-value = 0.000), both surgery and chemotropic baseline treatment patient (ϕ = 0.53; 95% CI(-1.12,-0.16), P-value = 0.009) significantly affected the survival of women breast cancer. Age of breast cancer patient, patient education level, place of residence, marital status, pre-existing comorbidity, axillary node status, estrogen receptor, tumor size, body mass index at diagnosis, stage of cancer, and baseline treatment were found to have a significant effect on time to survive for women with breast cancer at the University of Jimma Medical Center, Oromia region, Ethiopia. However, the covariate histologic grade, number of positive lymph nodes involved, and type of hormone used were insignificant to the survival of breast cancer patients.

Convenient method to improve efficiency of lymph node examination after gastrectomy with D2 lymphadenectomy for gastric cancer

BackgroundThe D2 procedure has been accepted as the standard treatment for advanced gastric cancer (GC) in East Asia. Determination of the number of lymph nodes (LNs) after gastrectomy may influence the pathological stage assessment of lymph node metastasis, significantly influencing prognostic evaluations and formulation of chemotherapy regimens.MethodsBetween January 2020 and January 2022, the medical files of 312 patients with clinical stage T0-4aN0-3M0 gastric cancer were reviewed retrospectively, and the patients were assigned to the normal group (lymph nodes were examined roughly), manual group (lymph nodes were manually examined meticulously), and device group (lymph nodes were examined by device). The clinical and pathologic characteristics, number of lymph nodes harvested, and the time required for lymph node examination was compared.ResultsA total of 312 gastric cancer patients (mean age 65.8 ± 10.3 years, 85 females and 227 males) underwent gastrectomy with curative intent at our department. Sex, age, body mass index (BMI), tumor size, clinical TNM stage, and pathologic TNM stage in the three groups showed no statistically significant differences (P > 0.05). The mean number of harvested lymph nodes in the normal, manual, and device group was 24.2, 36.6 and 35.2, respectively, which showed significant differences (P < 0.0001). The mean number of positive lymph nodes in the normal, manual, and device group was 3.5, 3.9 and 3.9, respectively (P = 0.99). The mean time consumption in device group was 15 min while the time consumption in manual group was 52.3 min, which showed a significant difference (P < 0.0001).ConclusionThis improved lymph node examination method offers a simple approach that is worth promoting, and it can improve the number of harvested lymph nodes efficiently.

Does gastric stump cancer really differ from primary proximal gastric cancer? A multicentre, propensity score matching-used, retrospective cohort study.

Although the location of proximal cancer of the remnant stomach is the same as that of primary proximal cancer of the stomach, its clinical characteristics and prognosis are still controversial. To evaluate the clinicopathological features and prognosis factors of gastric stump cancer (GSC) and primary proximal gastric cancer (PGC). From January, 2005 to December, 2016, 178 patients with GSC and 957 cases with PGC who received surgical treatment were enrolled. Patients in both groups underwent 1:1 propensity score matching analysis, and both clinical and pathological data were systematically collected for statistical purposes. Quality of life was evaluated by the C30 and STO22 scale between GSC-malignant (GSC following gastric cancer) and GSC-benign (GSC following benign lesions of the stomach). One hundred and fifty-two pairs were successfully matched after propensity score matching analysis. Of the 15 demographic and pathological variables collected, the analysis further revealed that the number of lymph nodes and positive lymph nodes were different prognostic and clinicopathological factors between PGC and GSC. Univariate and multivariate analyses showed that gender, differentiation degree and tumor-node-metastasis stage were independent risk factors for patients with GSC. Gender, vascular invasion, differentiation degree, depth of infiltration, positive lymph nodes, and tumor-node-metastasis stage were independent risk factors for patients with PGC. The 5-year overall survival and cancer-specific survival of patients with GSC were significantly lower than those in the PGC group, the scores for overall quality of life in the GSC-malignant group were lower than the GSC-benign, and the differences were statistically significant. The differences in clinicopathological characteristics between GSC and PGC were clarified, and PGC had a better prognosis than GSC.

OGC P18 10-year survival following oesophagectomy and 2-field lymphadenectomy: a retrospective cohort study

Abstract Background Only 12.6% of patients with oesophageal cancer in the UK will survive over 10 years. While oesophagectomy remains the best option for resectable oesophageal cancers, there is debate about the extent of lymphadenectomy during surgery and its impact on short and long-term outcomes. We analyzed the outcomes, including 5- and 10-year survivals, for patients undergoing oesophagectomy and radical lymphadenectomy by a single surgeon. Methods All patients who underwent oesophagectomy for any stage of oesophageal cancer in a single tertiary centre in the United Kingdom, with or without neoadjuvant chemotherapy, were identified from a prospectively maintained database from 2006-2017. We describe long term survival by number of lymph nodes resected and lymph node ratio (the ratio between the number of positive nodes and total nodes resected). Results Median survival following oesophagectomy was 66.3 months (95% CI: 53-71) with a minimum follow-up of 5 years. Most patients had adenocarcinomas (85.9%) followed by squamous carcinomas (8.5%). For all histologies, overall 5-year survival was 54% and 10-year survival was 40%. For patients with adenocarcinoma, resecting ≥24 lymph nodes improved survival compared with &amp;lt;24 nodes (median 73 months and 59 months respectively, p&amp;lt;0.038). The number of lymph nodes resected was an independent predictor of survival (p&amp;lt;0.001). For patients with any histology, a lower lymph node ratio indicated better survival (p&amp;lt;0.01). Conclusions This study demonstrates an improved long-term survival following oesophagectomy combined with lymphadenectomy of ≥24 nodes. We did not have any loss to follow-up with a long follow-up period, strengthening reported results.

Metastatic lymph node burden impacts overall survival in submandibular gland cancer.

To assess the effect of the number of positive lymph nodes (LNs) on the overall survival (OS) of patients with submandibular gland cancer (SmGC). Patients who had undergone neck dissection for SmGC were retrospectively enrolled in this study. The effect of the American Joint Committee on Cancer (AJCC) N stage, the number of positive LNs, LN size, LN ratio, and extranodal extension (ENE) on OS and recurrence-free survival (RFS) was evaluated using Cox analysis. Prognostic models were proposed based on the identified significant variable, and their performance was compared using hazard consistency and discrimination. In total, 129 patients were included in this study. The number of positive LNs rather than LN ratio, LN size, and ENE was associated with OS. A prognostic model based on the number of positive LNs (0 vs. 1-2 vs. 3+) demonstrated a higher likelihood ratio and Harrell's C index than those according to the 7th/8th edition of the AJCC N stage in predicting OS and RFS. The effect of LN metastasis on OS and RFS was mainly determined by the number of positive LNs. A validation of this finding is warranted in adenoid cystic carcinomas that were not included in this study.

Significance of tumor size and number of positive nodes in patients with FIGO 2018 stage IIIC1 cervical cancer.

This study aimed to investigate the prognostic significance of tumor size and number of positive pelvic lymph nodes (PLN) in International Federation of Gynecology and Obstetrics (FIGO) 2018 stage IIIC1 cervical cancer patients. Clinical data from 626 women with cervical cancer treated at Osaka International Cancer Center in 2010-2020 were retrospectively reviewed. Using the cutoff value obtained on the receiver operating characteristic analysis, the prognostic significance of tumor size and number of positive PLN in stage IIIC1 patients was first evaluated via uni- and multivariate analyses. Then, the impact of incorporating tumor size and number of positive PLN into the FIGO staging system was investigated using the Kaplan-Meier method. Among 196 women with Stage IIIC1 disease, larger tumors (>4cm) and multiple PLN metastases (≥4) were independent predictors of progression-free survival (PFS) in patients with stage IIIC1 cervical cancer. The PFS of patients with stage IIIC1 disease was inversely associated with the number of risk factors. Although patients with stage IIIC1 disease had significantly increased survival rates compared to those with stage IIIA or IIIB disease in the original FIGO 2018 staging system, this reversal phenomenon was resolved by incorporating larger tumors (>4cm) and multiple PLN metastases (≥4) into the revised staging system. Incorporating tumor size and number of metastatic lymph nodes into the FIGO staging system allows additional risk stratification for women with stage IIIC1 cervical cancer and improves survival prediction performance.

Comparative Effectiveness of Cetuximab Versus Panitumumab in Patients With Metastatic Colorectal Cancer: A Nationwide Database Study.

The study aimed to determine the effectiveness of cetuximab and panitumumab on the survival of patients with metastatic colorectal cancer or those who had undergone conversion surgery and to identify their prognostic factors. This retrospective cohort study used data from patients with metastatic colorectal cancer who received cetuximab or panitumumab as first-line targeted agent-based therapy. Overall survival and conversion surgery rates were evaluated, and the prognostic factors were determined. A total of 1,749 and 318 patients received cetuximab or panitumumab with chemotherapy, respectively. Overall survival and conversion surgery rates were similar between the cetuximab [hazard ratio (HR)=0.96] and panitumumab groups (HR=1.00). The prognostic factors associated with metastasectomy significantly lowered mortality among patients with metastatic colorectal cancer (HR=0.61). Older age (≥70 years), tumor stage 4B and 4C, right-sided tumors, mucinous adenocarcinoma, primary tumor resection, and the number of positive lymph nodes were associated with higher mortality and lower conversion surgery rates. Though panitumumab- and cetuximab-based therapies showed no differences, several factors, such as age over 70 years old, tumor stage 4B and 4C, undifferentiated carcinoma, mucinous carcinoma, right-sided tumor, number of positive lymph nodes, obstruction, and primary tumor resection increased the mortality risk of patients. This study underscores the importance of metastasectomy in current treatment guidelines and future clinical trials.

Preoperative Risk Factors for Lymphedema in Inflammatory Breast Cancer.

Prophylactic lymphatic bypass or LYMPHA (LYmphatic Microsurgical Preventive Healing Approach) is increasingly offered to prevent lymphedema following breast cancer treatment, which develops in up to 47% of patients. Previous studies focused on intraoperative and postoperative lymphedema risk factors, which are often unknown preoperatively when the decision to perform LYMPHA is made. This study aims to identify preoperative lymphedema risk factors in the high-risk inflammatory breast cancer (IBC) population. Retrospective review of our institution's IBC program database was conducted. The primary outcome was self-reported lymphedema development. Multivariable logistic regression analysis was performed to identify preoperative lymphedema risk factors, while controlling for number of lymph nodes removed during axillary lymph node dissection (ALND), number of positive lymph nodes, residual disease on pathology, and need for adjuvant chemotherapy. Of 356 patients with IBC, 134 (mean age: 51 years, range: 22-89 years) had complete data. All 134 patients underwent surgery and radiation. Forty-seven percent of all 356 patients (167/356) developed lymphedema. Obesity (body mass index > 30) (odds ratio [OR]: 2.7, confidence interval [CI]: 1.2-6.4, p = 0.02) and non-white race (OR: 4.5, CI: 1.2-23, p = 0.04) were preoperative lymphedema risk factors. Patients with IBC are high risk for developing lymphedema due to the need for ALND, radiation, and neoadjuvant chemotherapy. This study also identified non-white race and obesity as risk factors. Larger prospective studies should evaluate potential racial disparities in lymphedema development. Due to the high prevalence of lymphedema, LYMPHA should be considered for all patients with IBC.

Development of machine learning prognostic models for overall survival of prostate cancer patients with lymph node-positive

Prostate cancer (PCa) patients with lymph node involvement (LNI) constitute a single-risk group with varied prognoses. Existing studies on this group have focused solely on those who underwent prostatectomy (RP), using statistical models to predict prognosis. This study aimed to develop an easily accessible individual survival prediction tool based on multiple machine learning (ML) algorithms to predict survival probability for PCa patients with LNI. A total of 3280 PCa patients with LNI were identified from the Surveillance, Epidemiology, and End Results (SEER) database, covering the years 2000–2019. The primary endpoint was overall survival (OS). Gradient Boosting Survival Analysis (GBSA), Random Survival Forest (RSF), and Extra Survival Trees (EST) were used to develop prognosis models, which were compared to Cox regression. Discrimination was evaluated using the time-dependent areas under the receiver operating characteristic curve (time-dependent AUC) and the concordance index (c-index). Calibration was assessed using the time-dependent Brier score (time-dependent BS) and the integrated Brier score (IBS). Moreover, the beeswarm summary plot in SHAP (SHapley Additive exPlanations) was used to display the contribution of variables to the results. The 3280 patients were randomly split into a training cohort (n = 2624) and a validation cohort (n = 656). Nine variables including age at diagnosis, race, marital status, clinical T stage, prostate-specific antigen (PSA) level at diagnosis, Gleason Score (GS), number of positive lymph nodes, radical prostatectomy (RP), and radiotherapy (RT) were used to develop models. The mean time-dependent AUC for GBSA, RSF, and EST was 0.782 (95% confidence interval [CI] 0.779–0.783), 0.779 (95% CI 0.776–0.780), and 0.781 (95% CI 0.778–0.782), respectively, which were higher than the Cox regression model of 0.770 (95% CI 0.769–0.773). Additionally, all models demonstrated almost similar calibration, with low IBS. A web-based prediction tool was developed using the best-performing GBSA, which is accessible at https://pengzihexjtu-pca-n1.streamlit.app/. ML algorithms showed better performance compared with Cox regression and we developed a web-based tool, which may help to guide patient treatment and follow-up.

Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study.

Machine learning (ML) methods have shown great potential in predicting colorectal cancer (CRC) survival. However, the ML models introduced thus far have mainly focused on binary outcomes and have not considered the time-to-event nature of this type of modeling. This study aims to evaluate the performance of ML approaches for modeling time-to-event survival data and develop transparent models for predicting CRC-specific survival. The data set used in this retrospective cohort study contains information on patients who were newly diagnosed with CRC between December 28, 2012, and December 27, 2019, at West China Hospital, Sichuan University. We assessed the performance of 6 representative ML models, including random survival forest (RSF), gradient boosting machine (GBM), DeepSurv, DeepHit, neural net-extended time-dependent Cox (or Cox-Time), and neural multitask logistic regression (N-MTLR) in predicting CRC-specific survival. Multiple imputation by chained equations method was applied to handle missing values in variables. Multivariable analysis and clinical experience were used to select significant features associated with CRC survival. Model performance was evaluated in stratified 5-fold cross-validation repeated 5 times by using the time-dependent concordance index, integrated Brier score, calibration curves, and decision curves. The SHapley Additive exPlanations method was applied to calculate feature importance. A total of 2157 patients with CRC were included in this study. Among the 6 time-to-event ML models, the DeepHit model exhibited the best discriminative ability (time-dependent concordance index 0.789, 95% CI 0.779-0.799) and the RSF model produced better-calibrated survival estimates (integrated Brier score 0.096, 95% CI 0.094-0.099), but these are not statistically significant. Additionally, the RSF, GBM, DeepSurv, Cox-Time, and N-MTLR models have comparable predictive accuracy to the Cox Proportional Hazards model in terms of discrimination and calibration. The calibration curves showed that all the ML models exhibited good 5-year survival calibration. The decision curves for CRC-specific survival at 5 years showed that all the ML models, especially RSF, had higher net benefits than default strategies of treating all or no patients at a range of clinically reasonable risk thresholds. The SHapley Additive exPlanations method revealed that R0 resection, tumor-node-metastasis staging, and the number of positive lymph nodes were important factors for 5-year CRC-specific survival. This study showed the potential of applying time-to-event ML predictive algorithms to help predict CRC-specific survival. The RSF, GBM, Cox-Time, and N-MTLR algorithms could provide nonparametric alternatives to the Cox Proportional Hazards model in estimating the survival probability of patients with CRC. The transparent time-to-event ML models help clinicians to more accurately predict the survival rate for these patients and improve patient outcomes by enabling personalized treatment plans that are informed by explainable ML models.

Safety of double and a half layered esophagojejunal anastomosis in radical gastrectomy: A prospective, multi-center, single arm trial

Safety of double and a half layered esophagojejunal anastomosis in radical gastrectomy: A prospective, multi-center, single arm trial

Epidemiology and survival outcomes of colorectal mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinoma

BackgroundMixed neuroendocrine–non-neuroendocrine neoplasms are a rare subtype of neuroendocrine neoplasm consisting of ≥30% each of neuroendocrine and non-neuroendocrine differentiation. Neuroendocrine carcinomas are poorly differentiated neuroendocrine tumors. The epidemiology and prognosis of colorectal mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas are not clearly defined in the literature. We sought to examine the presentation, patterns of care, and outcomes of patients with mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas. MethodsWe identified patients diagnosed with stage I–III colorectal (excluding appendix) mixed neuroendocrine–non-neuroendocrine neoplasms or neuroendocrine carcinomas with only one-lifetime cancer diagnosis who underwent surgical resection between 2010 and 2018 from the National Cancer Database. We performed bidirectional selection to identify variables to include in a multivariable Cox proportional hazards model. ResultsWe identified 189 patients with a diagnosis of stage I to III colorectal mixed neuroendocrine–non-neuroendocrine neoplasms, 66% of whom had poorly differentiated tumors and 482 with neuroendocrine carcinomas. Among patients with stage III disease, 68% of patients with mixed neuroendocrine–non-neuroendocrine neoplasms and 54% of patients with neuroendocrine carcinomas received adjuvant chemotherapy. The median survival for the overall patients with mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas cohorts were 38 and 42 months, respectively (P = .22), and the median survival for patients with mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas with stage III disease were 30 and 25 months, respectively (P = .27). In multivariable analysis, fewer number of positive nodes and receipt of adjuvant chemotherapy were independently associated with decreased risk of mortality for patients with mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas. ConclusionAdjuvant chemotherapy is associated with improved survival in stage III mixed neuroendocrine–non-neuroendocrine neoplasms and neuroendocrine carcinomas. Future studies are warranted to identify subsets of patients benefiting most from adjuvant therapy.

Total Number of Lymph Nodes in Neck Dissection and Its Relation to Cancer-Positive Lymph Nodes as a Prognostic Indicator in Aerodigestive Tract Cancers: A Multi-Center Study.

Objectives Few studies have been conducted on the total number of lymph nodes (LNs) in neck dissection and the lymph node ratio (LNR; number of positive lymph nodes divided by number of excised lymph nodes), or their potential use as a prognostic indicator for cancers of the upper aerodigestive tract (UADT) and its treatment. We aimed to measure the number of lymph nodesdissected and the LNR to assess their prognostic value for cancers of the UADT, as well as their effect on overall survival and disease-free survival. Methods We performed a retrospective study of patients diagnosed with cancer of the UADT who underwent neck dissection as the primary or secondary modality of their treatment plan at King Abdulaziz University Hospital and the National Guard Hospital, Jeddah, Saudi Arabia. Data were collected through medical records and analyzed to assess prognosis and calculate survival rates in relation to the number of lymph nodes and LNR. Results A total of 121 patients were included: 14 women (11.57%) and 107 men (88.43%). The median age was 60 years and the mean follow-up period was 2.7 years. Of the malignancies, 44.63% were of the oral tongue and 35.54% were laryngeal. A median of 38 lymph nodes were dissected during neck dissections. The distribution of the individual LNRs was characterized by mean values. A mean LNR of 0.04 was considered the cutoff value, an LNR of > 0.04 a high LNR, and an LNR of < 0.04 a low LNR. Kaplan-Meier survival estimates for the cohort showed a three-year overall survival rate of 88% (95% confidence interval [CI]: 77% to 94%) for patients with a low LNR, but 71% (95% CI: 47% to 85%) for patients with a high LNR, which was statistically significant. A similar significant decreasing trend persisted at the four-year follow-up, where the disease-free survival rate was 73% (95% CI: 61% to 82%) for patients with a low LNR compared with 56% (95% CI: 35% to 72%) for patients with a high LNR. Conclusion The number of excised lymph nodes in neck dissections and the LNR might be a good prognostic indicator for overall survival and disease-free survival in patients with cancers of the UADT and may serve as a valuable tool in deciding on different treatment plans.

Performance of artificial intelligence-based algorithms to predict prolonged length of stay after head and neck cancer surgery

BackgroundMedical resource management can be improved by assessing the likelihood of prolonged length of stay (LOS) for head and neck cancer surgery patients. The objective of this study was to develop predictive models that could be used to determine whether a patient's LOS after cancer surgery falls within the normal range of the cohort. MethodsWe conducted a retrospective analysis of a dataset consisting of 300 consecutive patients who underwent head and neck cancer surgery between 2017 and 2022 at a single university medical center. Prolonged LOS was defined as LOS exceeding the 75th percentile of the cohort. Feature importance analysis was performed to evaluate the most important predictors for prolonged LOS. We then constructed 7 machine learning and deep learning algorithms for the prediction modeling of prolonged LOS. ResultsThe algorithms reached accuracy values of 75.40 (radial basis function neural network) to 97.92 (Random Trees) for the training set and 64.90 (multilayer perceptron neural network) to 84.14 (Random Trees) for the testing set. The leading parameters predicting prolonged LOS were operation time, ischemia time, the graft used, the ASA score, the intensive care stay, and the pathological stages. The results revealed that patients who had a higher number of harvested lymph nodes (LN) had a lower probability of recurrence but also a greater LOS. However, patients with prolonged LOS were also at greater risk of recurrence, particularly when fewer (LN) were extracted. Further, LOS was more strongly correlated with the overall number of extracted lymph nodes than with the number of positive lymph nodes or the ratio of positive to overall extracted lymph nodes, indicating that particularly unnecessary lymph node extraction might be associated with prolonged LOS. ConclusionsThe results emphasize the need for a closer follow-up of patients who experience prolonged LOS. Prospective trials are warranted to validate the present results.

Competing-risks model for predicting the prognostic value of lymph nodes in medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is an infrequent form malignant tumor with a poor prognosis. Because of the influence of competitive risk, there may suffer from bias in the analysis of prognostic factors of MTC. By extracting the data of patients diagnosed with MTC registered in the Surveillance, Epidemiology, and End Results (SEER) database from 1998 to 2016, we established the Cox proportional-hazards and competing-risks model to retrospectively analyze the impact of related factors on lymph nodes statistically. A total of 2,435 patients were included in the analysis, of which 198 died of MTC. The results of the multifactor competing-risk model showed that the number of total lymph nodes (19-89), positive lymph nodes (1-10,11-75) and positive lymph node ratio (25%-53%,>54%), age (46-60,>61), chemotherapy, mode of radiotherapy (others), tumor size(2-4cm,>4cm), number of lesions greater than 1 were poor prognostic factors for MTC. For the number of total lymph nodes, unlike the multivariate Cox proportional-hazards model results, we found that it became an independent risk factor after excluding competitive risk factors. Competitive risk factors have little effect on the number of positive lymph nodes. For the proportion of positive lymph nodes, we found that after excluding competitive risk factors, the Cox proportional-hazards model overestimates its impact on prognosis. The competitive risk model is often more accurate in analyzing the effects of prognostic factors. After excluding the competitive risk, the number of lymph nodes, the number of positive and the positive proportion are the poor prognostic factors of medullary thyroid cancer, which can help clinicians more accurately evaluate the prognosis of patients with medullary thyroid cancer and provide a reference for treatment decision-making.

Is radical radiotherapy with/without surgery an effective treatment in the lymphoepithelial carcinoma of the salivary gland？

BackgroundThere is limited information of radical radiotherapy (RT) on lymphoepithelial carcinoma of salivary gland (LECSG) regarding to the rarity of the disease. We conducted this retrospective study that evaluated the feasibility and efficacy of radical RT with/without surgery in LECSG.MethodsWe retrospectively reviewed patients that were pathologically diagnosed of LECSG and had definite or suspicious residual disease. The prescribed dose given to P-GTV and/or P-GTV-LN was 66 to 70.4 Gy. The clinical target volume (CTV) involved ipsilateral salivary gland and corresponding lymph node drainage area.ResultsA total of 56 patients were included. With a median follow-up of 60 months (range: 8 to 151 months), the 1-, 5-, and 10-year progression-free survival (PFS) rates were 94.6%, 84.7% and 84.7%; locoregional progression-free survival (LRPFS) rates were 98.2%, 87.4% and 87.4%; distance metastasis-free survival (DMFS) rates were 94.6%, 86.7% and 86.7%; and overall survival (OS) rates were 98.2%, 92.4% and 89.0%, respectively. A total of 7 patients without surgery were included. All patients were alive and only one patient experienced failure of distant metastasis four months after RT. The results of univariate analysis showed that compared with N stage, the number of positive lymph nodes (2 positive lymph nodes) was better prognostic predictor especially in PFS. There were no treatment-related deaths and most toxicities of RT were mild.ConclusionsRadical RT with/without surgery in LECSG for definite or suspicious residual disease is feasibility and efficacy. Most toxicities of RT were mild due to the target volume involved ipsilateral area.

Clinical analysis of cervical lymph node metastasis patterns and multivariate factors in differentiated thyroid carcinoma.

The incidence rate of thyroid cancer is rising rapidly in numerous parts of the world, but the mortality rate is relatively stable or even declining. The aim of the present study was to analyze the risk factors of cervical lymph node metastasis (LNM) in differentiated thyroid carcinoma (DTC). The clinical data of 846 patients with DTC were collected from the Department of General Surgery of Chifeng Municipal Hospital of Inner Mongolia Medical University (Chifeng, China) from June 2018 to June 2022. The relationship between central LNM (CLNM) and lateral LNM (LLNM) was explored in terms of sex, age, tumor diameter, multifocality, capsular invasion and Hashimoto's thyroiditis. It was revealed that male sex, age <35 years, tumor size >1 cm, multifocality and capsular invasion were associated with CLNM and LLNM (P<0.001), while there was no relationship between Hashimoto's thyroiditis, CLNM and LLNM (P>0.05). The number of positive lymph nodes in CLNM dissection, accounting for ≥50% of the total number of lymph nodes dissected, was significantly associated with LLNM (P<0.0001). In conclusion, there was no correlation between Hashimoto's thyroiditis and CLNM and LLNM. The present study revealed that patients with the characteristics of sex, age <35 years, tumor size >1 cm, multifocality and capsular invasion were associated with cervical LNM. The proportion of the number of central lymph node metastases to the total number of lymph nodes cleared during surgery is more than or equal to 50%, indicating a susceptibility to external cervical lymph node metastasis. The results of multivariate logistic analysis showed that male sex, multifocality, capsular invasion and CLNM were risk factors for LLNM, and age was a protective factor for LLNM in DTC.

The Number of Positive Lymph Nodes as Prognostic Factor in ypN1 Breast Cancer with Neoadjuvant Chemotherapy

This study aimed to assess the ability of the number of positive lymph nodes (LNP) after neoadjuvant chemotherapy (NAC) to stratify prognosis even within the same ypN stage in breast cancer patients. A 6,443 non-metastatic breast cancer patients with ypN1 disease after NAC following primary surgery were identified using the stage, stage evaluation field, treatment fields from Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed for overall survival (OS) using Kaplan-Meier plot and Cox proportional hazard models. Of patients, 1,132(17.6%) had 3 positive lymph nodes (LNP3), 4,363 (67.7%) patients were T1/2 stage and 538 (8.35%) patients were downstage after treatment. LNP3 group had a significantly worse OS than LNP1/2 group (5yr OS, 74.2% vs. 80.9%, p <0.001). Similar results were observed in cause specific survival analysis (5yr OS, 79.8% vs. 85.2%, p <0.001). In subgroup analysis, there was a significant difference in OS between LNP1/2 and LNP3 group for HER2 or triple negative subtype, (p <0.001), T1/2 stage (p <0.001) and stable/downstage of N stage (p <0.001 and 0.019, respectively), but not for luminal A/B subtype and T3/4 (p = 0.126, 0.629 and 0.154, respectively). Regarding the number of examined lymph node (LNE), OS was significantly decreased in patients with LNE ≤5 in LNP3 group (p <0.001) but not in LNP1/2 group. In multivariable analysis, the prognostic significance of LNP3 remained (p <0.001) and the following factors were significantly related to the prolonged OS; Luminal A/B (p<0.001 and 0.001, respectively), T1/2 stage (p <0.001), N1 stage (p <0.001), LNE (≤5 vs. >5, p = 0.001) and receipt of radiotherapy (p = 0.012). Even when PS matching was performed, the OS of LNP was worse than that of LNP1/2. LNP could more stratify the patients with ypN1 breast cancer after NAC. LNP3 is significantly associated with OS even after adjusting for other prognosticators. In particular, since there is a potential difference in the magnitude of the impact of LNP3 according to LNE, it is necessary to consider both of them together for decision-making.

Clinico-Genomics Model to Predict Survival in Non-Metastatic Breast Cancer: Comparing the Performance of Machine Learning Models

Breast cancer is a heterogenous spectrum of disease with variable outcome. This heterogeneity of outcome could be driven by underlying heterogeneity in the genotypes. There remains an unmet need of defining prognosis based on underlying genetic heterogeneity. The primary objective of this study was to build a combined clinic-genomics model to predict overall survival (OS) in patients with non-metastatic breast cancer. The Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database is a combined Canada-UK Project which contains information on 31 demographic, clinical and treatment characteristics in addition to m-RNA level z-score for 331 genes for 1904 breast cancer patients. We excluded patients with metaplastic breast cancer (n = 1) or unknown histologic subtype (n = 13), and those with missing information on breast surgery (n = 22) and cellularity (n = 54). Demographic characteristics included age of the patient and menopausal status while clinical characteristics included tumor stage, number of positive lymph nodes, pathologic grade, cellularity, receptor status for estrogen and progesterone receptors, and HER2neu gene amplification status. Treatment included type of breast cancer surgery, chemotherapy, hormone therapy, and radiation therapy. The data was split randomly at an 80:20 ratio into training and testing dataset. Subsequently, two cross-validated supervised machine learning algorithms were applied to build the prognostic model - elastic net logistic regression and random forest classifier. We compared the performance of the models in the testing dataset using area under receiver operating curve (AUC). All analysis were done using sparklyr - an R interface to Apache SparkTM. Overall, 1814 patients were included in the analysis. The AUC for elastic net logistic regression model and random forest classifier was 0.74, and 0.73, respectively. The sensitivity and specificity of the elastic net logistic regression model was 0.84 and 0.45, respectively while those for the random forest classifier was 0.83 and 0.51, respectively. STAT5A, CASP8, HSD17b11, and CDKN2c were common to the list of important genes predicting OS in both models while age, lymph node count, Nottingham Prognostic Index (NPI), and type of breast surgery were common to the list of clinical factors predicting OS in both models. This study shows that a multivariable prognostic model with combination of clinical and demographic parameters with Z-score expression data can predict for overall survival.