Risk Factors For Lymph Node Metastasis Research Articles

Machine learning predictive models and risk factors for lymph node metastasis in non-small cell lung cancer

BackgroundThe prognosis of non-small cell lung cancer (NSCLC) is substantially affected by lymph node metastasis (LNM), but there are no noninvasive, inexpensive methods of relatively high accuracy available to predict LNM in NSCLC patients.MethodsClinical data on NSCLC patients were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors for LNM were recognized LASSO and multivariate logistic regression. Six predictive models were constructed with machine learning based on risk factors. The area under the receiver operating characteristic curve (AUC) was used to assess the performance of the model. Subgroup analysis with different T-stages was performed on an optimal model. A webpage LNM risk calculator for optimal model was built using the Shinyapps.io platform.ResultsWe enrolled 64,012 NSCLC patients, of whom 26,611 (41.57%) had LNM. Using multivariate logistic regression, we finally identified 10 independent risk factors for LNM: age, sex, race, histology, primary site, grade, T stage, M stage, tumor size, and bone metastases. GLM is the optimal model among all six machine learning models in both the training and validation cohorts. Subgroup analyses revealed that GLM has good predictability for populations with different T staging. A webpage LNM risk calculator based on GLM was posted on the shinyapps.io platform (https://wubopredict.shinyapps.io/dynnomapp/).ConclusionThe predictive model based on GLM can be used to precisely predict the probability of LNM in NSCLC patients, which was proven effective in all subgroup analyses according to T staging.

Histological Risk Factors for Lymph Node Metastasis in pT1 Colorectal Cancer: Does Submucosal Invasion Depth Really Matter?

After endoscopic resection of colorectal cancer with submucosal invasion (pT1 CRC), additional surgical treatment is recommended if deep submucosal invasion (DSI) is present. This study aimed to further elucidate the risk factors for lymph node metastasis (LNM) in patients with pT1 CRC, especially the effect of DSI on LNM. Patients with pT1 CRC who underwent lymph node dissection were selected. The Chi-square test and multivariate logistic regression were used to analyze the relationship between clinicopathological characteristics and LNM. The submucosal invasion depth (SID) was measured via 4 methods and analyzed with 3 cut-off values. Twenty-eight of the 239 patients presented with LNM (11.7%), and the independent risk factors for LNM included high histological grade (P=0.003), lymphovascular invasion (LVI) (P=0.004), intermediate to high budding (Bd 2/3) (P=0.008), and cancer gland rupture (CGR) (P=0.008). Moreover, the SID, width of submucosal invasion (WSI), and area of submucosal invasion (ASI) were not significantly different. When one, two, three or more risk factors were identified, the LNM rates were 1.1% (1/95), 12.5% (7/56), and 48.8% (20/41), respectively. Indicators such as the SID, WSI, and ASI are not risk factors for LNM and are subjective in their measurement, which renders them relatively inconvenient to apply in clinical practice. In contrast, histological grade, LVI, tumor budding and CGR are relatively straightforward to identify and have been demonstrated to be statistically significant. It would be prudent to focus on these histological factors rather than subjective measurements.

Re-evaluation of the role of endoscopic submucosal dissection in the treatment of early gastric cancer based on additional gastrectomy results.

Endoscopic submucosal dissection (ESD) plays a pivotal role in treating early gastric cancer (EGC). Some patients require additional gastrectomy because of non-curative ESD. This study aimed to analyze the clinical factors associated with non-curative ESD and to re-evaluate the role of ESD according to its indication criteria. Altogether, 134 patients who had undergone additional gastrectomy with lymphadenectomy for non-curative ESD based on the pathological results of ESD specimens were included. Their data including pre-ESD diagnosis, reasons for requesting additional gastrectomy, and surgical outcomes were analyzed retrospectively. Of the 134 patients with EGC in the final pathology of ESD specimens, 56 underwent staging ESD for a diagnostic approach, of whom 28 were diagnosed with atypical glands and 28 with high-grade dysplasia (HGD) prior to ESD. The remaining 78 patients of the 134 were identified to have EGC and received ESD for therapy. Based on the pathological results of ESD specimens, additional gastrectomy was commissioned with non-curative ESD because of one or more causes such as deep submucosal invasion, lymphatic invasion, positive vertical margin, undifferentiated histology, positive lateral margin, and venous invasion. Regarding surgical specimens, 13 patients had lymph node metastasis (LNM) and 9 had local residual tumor; one of them had both LNM and a local residual tumor. In patients with atypical glands, 4 had LNM and 3 had a local residual tumor; one of them had both LNM and a local residual tumor, and then died of multiple organ metastasis. In patients with HGD, 4 had LNM and 1 had a local residual tumor. Additionally, 4 patients who were absolutely indicated for ESD had LNM, of whom 2 had atypical glands, and the other 2 had HGD. Similarly, in 6 patients with a local residual tumor absolutely indicated for ESD, 2 had atypical glands and 1 had HGD. Positive vertical margin, lymphatic invasion, and deep submucosal invasion were identified as independent risk factors for LNM. ESD may play diagnostic and therapeutic roles in determining the optimal treatment of EGC when the diagnosis is equivocal or insufficient in endoscopic assessments for gastric cancer screening.

Construction and validation of a nomogram model for lymph node metastasis of stage II-III gastric cancer based on machine learning algorithms.

Gastric cancer, a pervasive malignancy globally, often presents with regional lymph node metastasis (LNM), profoundly impacting prognosis and treatment options. Existing clinical methods for determining the presence of LNM are not precise enough, necessitating the development of an accurate risk prediction model. Our primary objective was to employ machine learning algorithms to identify risk factors for LNM and establish a precise prediction model for stage II-III gastric cancer. A study was conducted at Renji Hospital Affiliated to Shanghai Jiao Tong University School of Medicine between May 2010 and December 2022. This retrospective study analyzed 1147 surgeries for gastric cancer and explored the clinicopathological differences between LNM and non-LNM cohorts. Utilizing univariate logistic regression and two machine learning methodologies-Least absolute shrinkage and selection operator (LASSO) and random forest (RF)-we identified vascular invasion, maximum tumor diameter, percentage of monocytes, hematocrit (HCT), and lymphocyte-monocyte ratio (LMR) as salient factors and consolidated them into a nomogram model. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves were used to evaluate the test efficacy of the nomogram. Shapley Additive Explanation (SHAP) values were utilized to illustrate the predictive impact of each feature on the model's output. Significant differences in tumor characteristics were discerned between LNM and non-LNM cohorts through appropriate statistical methods. A nomogram, incorporating vascular invasion, maximum tumor diameter, percentage of monocytes, HCT, and LMR, was developed and exhibited satisfactory predictive capabilities with an AUC of 0.787 (95% CI: 0.749-0.824) in the training set and 0.753 (95% CI: 0.694-0.812) in the validation set. Calibration curves and decision curves affirmed the nomogram's predictive accuracy. In conclusion, leveraging machine learning algorithms, we devised a nomogram for precise LNM risk prognostication in stage II-III gastric cancer, offering a valuable tool for tailored risk assessment in clinical decision-making.

Predictive Biomarkers of Lymph Node Metastasis in Early Gastric Cancer: A Reference of Clinicopathological Characteristics, Protein Expression, Epstein-Barr Virus Status, and Microsatellite Instability.

Predicting lymph node metastasis (LNM) in early gastric cancer (EGC) is crucial for making treatment decisions. This study aimed to confirm risk factors for LNM and identify novel auxiliary biomarkers for predicting LNM in EGC. We established a training set, comprising 63 patients with LNM-EGC and 274 patients with non-LNM EGC, and a test set, comprising 19 patients with LNM-EGC and 146 non-LNM EGC. Immunohistochemistry for lymphangiogenic and related pathway components (VEGF-C, TGF-β1, SMAD2/3, VEGF-D, pSTAT3, E-cadherin, CD44, c-MET, YAP, and HER2), in situ hybridization for Epstein-Barr virus-encoded small RNAs, and multiplex PCR for microsatellite instability were conducted. In the training set, Lauren's diffuse/mixed classification, stromal desmoplasia, submucosal invasion ≥500 μm, lymphatic invasion, and high VEGF-C and SMAD2/3 expression were independent risk factors for LNM (p<0.05). A large tumor size, mixed histology, submucosal invasion, perineural invasion, and ulceration were determined as risk factors using univariate analysis (p<0.05). The tumor cutoff size for predicting LNM was 2.65 cm, based on a ROC analysis. The test set study verified that stromal desmoplasia, submucosal invasion, and high VEGF-C expression were independent risk factors for LNM (p<0.05). Moreover, mixed histology, lymphatic invasion, ulceration, and high SMAD 2/3 expression were identified as additional risk factors using univariate analysis (p<0.05). Stromal desmoplasia, submucosal invasion, and high VEGF-C expression are potential biomarkers for LNM in EGC. VEGF-C expression might serve as an adjunct biomarker for predicting LNM on forceps-biopsy tissue at initial diagnosis.

Latest guideline of endoscopic submucosal dissection of early gastric cancer may not be suitable for Chinese patients: retrospective study findings from two centers.

To analyze the diagnostic efficiency of the four absolute endoscopic submucosal dissection (ESD) indications for lymph node metastasis (LNM) of Chinese patients with early gastric cancer (EGC). We retrospectively analyzed EGC patients who underwent radical D2 gastrectomy from January 2019 to December 2022. We evaluated the rate of LNM, false-negative rate, and negative predictive value of the four ESD indications. Of enrolled 2722 EGC patients, 388 (14.3%) patients presented LNM. Tumor size > 2 cm, ulceration, submucosal invasion, undifferentiated type, and lymphovascular invasion were independent risk factors of LNM in patients with EGC. 1062 (39%) cases of EGC conformed to the four EDS indications; however, 4% of them had LNM. 451 cases were fully in accord with the fourth ESD indication (undifferentiated intramucosal carcinoma without ulceration and a maximum lesion diameter of ≤ 2 cm), and 35 of them had LNM, with a false-negative rate (FNR) of 9.02% and a negative predictive value (NPV) of 92.24%. There was significant difference among the four indications in terms of the rate of LNM (1.0% vs 1.5% vs 1.3% vs 7.8%, P < 0.001), FNR (1.03% vs 0.52% vs 0.26% vs 9.02%, P < 0.001), and NPV (98.99% vs 98.53% vs 98.75% vs 92.24%, P < 0.001). Overall, the fourth ESD indication was associated with a high rate of LNM compared to the other three indications. Thus, it might not be safe to classify it as an absolute indication in Chinese patients with EGC.

Nodal Metastasis in Oral Squamous Cell Carcinoma: an Analysis of Risk Factors and Influence on Overall Survival

Introduction: Oral squamous cell carcinoma (OSCC) presents a high tendency of lymph node metastasis (LNM). Objective: Determine which risk factors play a significant role in metastasis to cervical lymph nodes and to evaluate the influence of nodal involvement on overall survival of patients with OSCC. Method: Medical records of 350 patients with OSCC were retrospectively reviewed. The data were analyzed using the chi-square, Fisher’s exact and log-rank Mantel Cox tests and multinomial and Cox logistic regression. Results: Of the 350 medical records evaluated, 251 reported N0, 75 N1, 16 N2 and 8 N3. Male gender, referrals from private health care providers, T3/4 stage and non-surgical treatments were associated with LNM. In multivariate analysis, men and T3/4 tumors were shown to be independent risk factors for LNM. The independent risk factors for survival were male gender, nodal involvement (p = 0.017) and non-surgical treatment. Conclusion: Male gender and T-stage are risk factors for LNM in patients with OSCC. Moreover, the presence of LNM and age &gt;65 years are associated with poor overall survival.urvivor.

Lymphovascular invasion is a dominant risk factor for lymph node metastasis in T2 rectal cancer.

Background and study aims Surgical resection is standard treatment of T2 rectal cancer due to risk of concomitant lymph node metastases (LNM). Local resection could potentially be an alternative to surgical treatment in a subgroup of patients with low risk of LNM. The aim of this study was to identify clinical and histopathological risk factors of LNM in T2 rectal cancer. Patients and methods This was a retrospective registry-based population study on prospectively collected data on all patients with T2 rectal cancer undergoing surgical resection in Sweden between 2009 and 2021. Potential risk factors of LNM, including age, gender, resection margin, lymphovascular invasion (LVI), histologic grade, mucinous cancer, and perineural invasion (PNI) were analyzed using univariate and multivariate logistic regression. Results Of 1607 patients, 343 (21%) with T2 rectal cancer had LNM. LVI (odds ratio [OR] = 4.21, P < 0.001) and age < 60 years (OR = 1.80, P < 0.001) were significant and independent risk factors. However, PNI (OR = 1.50, P = 0.15), mucinous cancer (OR = 1.14, P = 0.60), histologic grade (OR = 1.47, P = 0.07) and non-radical resection margin (OR = 1.64, P = 0.38) were not significant risk factors for LNM in multivariate analyses. The incidence of LNM was 15% in the absence of any risk factor. Conclusions This was a large study on LNM in T2 rectal cancer which showed that LVI is the dominant risk factor. Moreover, low age constituted an independent risk factor, whereas gender, resection margin, PNI, histologic grade, and mucinous cancer were not independent risk factors of LNM. Thus, these findings may provide a useful basis for management of patients after local resection of early rectal cancer.

Omission of axillary surgery in cN0, postmenopausal ER-positive/HER2-negative breast cancer patients undergoing breast-conserving treatment.

Previous clinical trials have diminished the significance of lymph node (LN) metastasis and axillary surgery in breast cancer, particularly in cN0, postmenopausal estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative patients undergoing breast-conserving treatment (BCT). We assessed the replacement of axillary surgery with preoperative imaging modalities by analyzing the proportion of high nodal burden (HNB) patients with ≥3 LN metastases in these patients. We retrospectively identified 333 cN0, postmenopausal ER-positive/HER2-negative breast cancer patients who underwent BCT in two hospitals between January 2003 and December 2017. The proportion of LN metastasis patients and the number of metastatic LN were investigated. Risk factors of LN metastasis were analyzed and recurrence-free survival (RFS) was compared. Axillary surgery confirmed LN metastasis in 81 (24.3%) of the cN0 patients. The clinical tumor size (cT) and age were factors associated with LN metastasis [cT: odds ratio (OR), 2.92, 95% confidence interval (CI): 1.69-5.05, P<0.001; age: OR, 0.33, 95% CI: 0.11-0.99, P=0.048]. However, HNB patients with ≥3 LN metastases were 15 (4.5%) of all the patients. There was statistically significant difference in the incidence of HNB between patients with cT1 tumors (3.6%) and those with cT2 tumors (7.4%) (P<0.001). In cN0, postmenopausal ER-positive/HER2-negative patients who underwent BCT, patients with cT1 tumors had lower rate of LN metastasis, and there were fewer instances of HNB. Therefore, in these patients, omission of axillary surgery including SLNB can be carefully considered.

Low Absolute Lymphocyte Count Correlates with Lymph Node Metastases and Worse Survival of Patients with Gastric Cancer.

Several studies have found that the absolute lymphocyte (ALC) or neutrophil count predicts the survival of patients with solid tumors, and that the neutrophil-to-lymphocyte ratio and the prognostic nutritional index are useful markers of gastric cancer prognosis. However, it remains unclear whether the ALC is prognostic of lymph node (LN) metastasis in patients with gastric cancer. In this study, we aimed to explore the impact of ALC on prognosis and distinctive clinical characteristics in patients with gastric cancer. The medical records of patients with gastric adenocarcinomas who underwent radical gastrectomy with curative intent at Seoul St. Mary's Hospital and Yeouido St. Mary's Hospital between January 2010 and December 2017 were reviewed. Of these, 4149 patients for whom preoperative white blood cell, neutrophil, and lymphocyte counts were available were enrolled. In all 4149 patients, ALC gradually decreased as the pN stage increased. Those with an ALC of less than 1360 cells/μL were defined as a low-ALC group, and advanced cT and cN stages were the strongest risk factors for LN metastasis in both univariate and multivariate analyses; undifferentiated tumor histology and a low ALC were also significant risk factors. Patients of all stages in the ALC-low group exhibited poorer prognoses. The ALC-low group also exhibited a higher recurrence rate in a greater proportion of LNs. In patients with gastric cancer, as the preoperative ALC decreases, the incidence of LN metastasis increases. A low ALC is associated with a high recurrence rate, particularly in LNs.

Clinical outcomes after endoscopic resection and the risk of lymph node metastasis in rectal neuroendocrine tumors: a single-center retrospective study.

The incidence of rectal neuroendocrine tumors (R-NETs) has increased in recent years. However, the predictors of lymph node (LN) metastasis and clinical outcomes, particularly following endoscopic treatment, remain unclear. Our study aims to elucidate the potential risk factors for LN metastasis and the clinical outcomes of patients undergoing endoscopic resection in R-NETs. A total of 128 patients with R-NETs were retrospectively identified from a single center between June 2012 and December 2021. Risk factors for LN metastasis in R-NETs were analyzed using multivariate analysis. Additionally, the clinical outcomes of endoscopic resections in patients with R-NETs were assessed. In our study, 128 patients with R-NETs were retrospectively analyzed. The risk factors for LN metastasis determined by multivariate analysis were tumor size and patient age at diagnosis. Among the 111 patients treated with endoscopic resection and with tumor margin records available, 92 underwent endoscopic submucosal dissection (ESD) and 19 underwent conventional endoscopic mucosal resection (EMR). There was no significant difference between the two groups regarding the positive rates of basal tumor margin and lateral tumor margin. Furthermore, 64 patients who underwent endoscopic resection for R-NETs were successfully followed up (range, 1.64-76.71months), during which only one patient developed local recurrence. Tumor size and age at diagnosis were predictors for LN metastasis of R-NETs. Both ESD and EMR are alternative techniques with a favorable prognosis for R-NETs, even in cases with positive resection margins. However, due to the relatively small number of patients undergoing EMR and missing data in follow-up protocols, definitive conclusions require further large-scale studies.

Tumor thickness as a novel risk factor for lymph node metastasis by superficial squamous cell carcinoma of head and neck.

Narrow-band imaging combined with magnified endoscopy has enabled the detection of superficial squamous cell carcinoma of the head and neck (SSCCHN) that has been resected with minimally invasive treatment, preserving vocalization and swallowing functions. However, risk factors of lymph node metastasis (LNM) must be identified, as some patients with LNM have a poor prognosis. From an initial 599 patients with 700 lesions who underwent trans-oral surgery in 27 Japanese hospitals (a nationwide registration survey), we enrolled 541 patients with 633 SSCCHNs, as indicated by central pathological diagnoses. All pathological specimens for each patient were examined using 20 pathological factors that are thought to affect the LNM of SSCCHN. In all, 24 (4.4%) of the 568 SSCCHNs exhibited LNM, and all 24 had at least one solitary nest of epithelial neoplastic cells present in the stroma, clearly separated from the intraepithelial carcinoma. Multivariate analysis also showed that tumor thickness (p = 0.0132, RR: 7.85, 95% confidence interval [CI]: 1.54-40.02), and an INFc pattern classified as infiltrating growth (INF) with unclear boundaries between tumor and non-tumor tissues (p = 0.0003, RR: 14.47, 3.46-60.46), and tumor budding (p = 0.0019, RR: 4.35, CI: 1.72-11.01) were significantly associated with LNM. Solitary nests may be indicative of LNM. In addition, tumor thickness was revealed to be a risk factor for LNM in SSCCHNs using pT factors that do not include an invasion depth element because of the anatomical absence of the muscularis mucosae.

Development and validation of a nomogram for predicting lymph node metastasis in early gastric cancer.

Lymph node metastasis (LNM) significantly impacts the treatment and prognosis of early gastric cancer (EGC). Consequently, the precise prediction of LNM risk in EGC patients is essential to guide the selection of appropriate surgical approaches in clinical settings. To develop a novel nomogram risk model for predicting LNM in EGC patients, utilizing preoperative clinicopathological data. Univariate and multivariate logistic regression analyses were performed to examine the correlation between clinicopathological factors and LNM in EGC patients. Additionally, univariate Kaplan-Meier and multivariate Cox regression analyses were used to assess the influence of clinical factors on EGC prognosis. A predictive model in the form of a nomogram was developed, and its discrimination ability and calibration were also assessed. The incidence of LNM in the study cohort was 19.6%. Multivariate logistic regression identified tumor size, location, degree of differentiation, and pathological type as independent risk factors for LNM in EGC patients. Both tumor pathological type and LNM independently affected the prognosis of EGC. The model's performance was reflected by an area under the curve of 0.750 [95% confidence interval (CI): 0.701-0.789] for the training group and 0.763 (95%CI: 0.687-0.838) for the validation group. A clinical prediction model was constructed (using tumor size, low differentiation, location in the middle-lower region, and signet ring cell carcinoma), with its score being a significant prognosis indicator.

Preoperative computed tomography semantic features in predicting lymph node metastasis of part-solid nodules in non-small cell lung cancer: a multicenter retrospective study.

Lymph node metastasis (LNM) is the most common route of metastasis for lung cancer, and it is an independent risk factor for long-term survival and recurrence in patients with non-small cell lung cancer (NSCLC). The purpose of this study was to explore the value of preoperative computed tomography (CT) semantic features in the differential diagnosis of LNM in part-solid nodules (PSNs) of NSCLC. A total of 955 patients with NSCLC confirmed by postoperative pathology were retrospectively enrolled from January 2019 to March 2023. The clinical, pathological data and preoperative CT images of these patients were investigated and statistically analyzed in order to identify the risk factors for LNM. Multivariate logistic regression was used to select independent risk factors and establish different prediction models. Ten-fold cross-validation was used for model training and validation. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated, and the Delong test was used to compare the predictive performance between the models. LNM occurred in 68 of 955 patients. After univariate analysis and adjustment for confounding factors, smoking history, pulmonary disease, solid component proportion, pleural contact type, and mean diameter were identified as the independent risk factors for LNM. The image predictors model established by the four independent factors of CT semantic features, except smoking history, showed a good diagnostic efficacy for LNM. The AUC in the validation group was 0.857, and the sensitivity, specificity, and accuracy of the model were all 77.6%. Preoperative CT semantic features have good diagnostic value for the LNM of NSCLC. The image predictors model based on pulmonary disease, solid component proportion, pleural contact type, and mean diameter demonstrated excellent diagnostic efficacy and can provide non-invasive evaluation in clinical practice.

[18F]FAPI adds value to [18F]FDG PET/CT for diagnosing lymph node metastases in stage I-IIIA non-small cell lung cancer: a prospective study

BackgroundThis study investigates the value of fluorine 18 ([18F])-labeled fibroblast activation protein inhibitor (FAPI) for lymph node (LN) metastases in patients with stage I-IIIA non-small cell lung cancer (NSCLC).MethodsFrom November 2021 to October 2022, 53 patients with stage I-IIIA NSCLC who underwent radical resection were prospectively included. [18F]-fluorodeoxyglucose (FDG) and [18F]FAPI examinations were performed within one week. LN staging was validated using surgical and pathological findings. [18F]FDG and [18F]FAPI uptake was compared using the Wilcoxon signed-ranks test. Furthermore, the diagnostic value of nodal groups was investigated.ResultsIn 53 patients (median age, 64 years, range: 31–76 years), the specificity of [18F]FAPI for detecting LN metastasis was significantly higher than that of [18F]FDG (P < 0.001). High LN risk category, greater LN short-axis dimension(≥ 1.0 cm), absence of LN calcification or high-attenuation, and higher LN FDG SUVmax (≥ 10.1) were risk factors for LN metastasis(P < 0.05). The concurrence of these four risk factors accurately predicted LN metastases (Positive Predictive Value [PPV] 100%), whereas the presence of one to three risk factors was unable to accurately discriminate the nature of LNs (PPV 21.7%). Adding [18F]FAPI in this circumstance improved the diagnostic value. LNs with an [18F]FAPI SUVmax<6.2 were diagnosed as benign (Negative Predictive Value 93.8%), and LNs with an [18F]FAPI SUVmax≥6.2 without calcification or high-attenuation were diagnosed as LN metastasis (PPV 87.5%). Ultimately, the integration of [18F]FDG and [18F]FAPI PET/CT resulted in the highest accuracy for N stage (83.0%) and clinical decision revisions for 29 patients.ConclusionIn patients with stage I-IIIA NSCLC, [18F]FAPI contributed additional valuable information to reduce LN diagnostic uncertainties after [18F]FDG PET/CT. Integrating [18F]FDG and [18F]FAPI PET/CT resulted in more precise clinical decisions.Trial registrationThe Chinese Clinical Trial Registry: ChiCTR2100044944 (Registered: 1 April 2021, https://www.chictr.org.cn/showprojEN.html?proj=123995).

The value of dual time-point fluorine-18 fluorodeoxyglucose PET/computed tomography imaging in predicting lymph node metastasis in non-small cell lung cancer patients.

The purpose of this study was to analyze the correlation between specified dual time-point fluorine-18 fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (CT) imaging parameters and pathological characteristics in non-small cell lung cancer (NSCLC) patients. This study retrospectively analyzed 47 patients with NSCLC. All patients underwent dual time-point 18 F-FDG PET/CT imaging. We obtained the metabolic parameters, standardized uptake value (SUV) maximum, SUV mean , delayed standardized uptake value (DSUV) maximum, DSUV mean , delay index standardized uptake value (DISUV) maximum, and DISUV mean , of the primary tumor. The tumor size was measured by CT. All lymph nodes had a definite pathological diagnosis. We next evaluated the status of the lymph node metastases (LNM) and the correlations between metabolic parameters and clinical characteristics. Receiver operating characteristic curves were drawn for the prediction of LNM. We found that the DSUV max , DISUV max , DSUV mean , and tumor size were significantly related to LNM ( P = 0.036, 0.009, and 0.049, respectively). Multivariate analysis revealed that tumor size and DISUV max were independent risk factors for LNM in lung cancer patients. According to the receiver operating characteristic curve analysis, the optimal cutoff values for DISUV max and tumor size were 0.33 and 2.8 cm, respectively. When these two parameters were combined, the area under the curve for predicting LNM in NSCLC was 0.768, and the sensitivity was 95.7% for predicting LNM in lung cancer patients. We further allocated the patients to three groups: the high-risk group (tumor size ≥ 2.8 cm, DISUV max ≥ 0.33), the moderate-risk group (tumor size ≥ 2.8 cm, DISUV max < 0.33, or tumor size < 2.8 cm, DISUV max ≥ 0.33), and the low-risk group (tumor size < 2.8 cm, DISUV max < 0.33). The rates of LNM were 70, 50, and 0%, respectively. Tumor size and DISUV max are risk factors for predicting LNM, and they are more useful in combination. Compared with standard PET/CT imaging, dual time-point PET/CT imaging has added value in predicting LNM in NSCLC patients.

Preoperative prediction of lymph node metastasis in colorectal cancer using 18F-FDG PET/CT peritumoral radiomics analysis.

Radiomics has been used in the diagnosis of tumor lymph node metastasis (LNM). However, to date, most studies have been based on intratumoral radiomics. Few studies have focused on the use of 18F-fluorodeoxyglucose positron emission computed tomography (18F-FDG PET/CT) peritumoral radiomics for the diagnosis of LNM in colorectal cancer (CRC). Determining the value of radiomics features extracted from 18F-FDG PET/CT images of the peritumoral region in predicting LNM in patients with CRC. The clinical data and preoperative 18F-FDG PET/CT images of 244 CRC patients were retrospectively analyzed. Intratumoral and peritumoral radiomics features were screened using the mutual information method, and least absolute shrinkage and selection operator regression. Based on the selected radiomics features, a radiomics score (Rad-score) was calculated, and independent risk factors obtained from univariate and multivariate logistic regression analyses were used to construct clinical and combined (Radiomics + Clinical) models. The performance of these models was evaluated using the DeLong test, while their clinical utility was assessed by decision curve analysis. Finally, a nomogram was constructed to visualize the predictive model. The most optimal set of features retained by the feature filtering process were all peritumoral radiomic features. Carcinoembryonic antigen levels, PET/CT-reported lymph node status and Rad-score were found to be independent risk factors for LNM. All three LNM risk assessment models exhibited good predictive performance, with the combined model showing the best classification results, with areas under the curve of 0.85 and 0.76 in the training and validation groups, respectively. The DeLong test revealed that the performance of the combined model was superior to that of the clinical and radiomics models in both the training and validation groups, although this difference was only statistically significant in the training group. DCA indicated that the combined model displayed better clinical utility. 18F-FDG PET/CT peritumoral radiomics is uniquely suited to predict the presence of LNM in patients with CRC. In particular, the predictive efficacy of LNM for precision therapy and individualized patient management can be improved by using a combination of clinical risk factors.

Preoperatively predicting thelymphnodemetastasis and prognosis for gastric cancer patients.

The preoperative distinguishment of lymph nodes (LN) with metastasis plays a pivotal role in guiding the surgical extension for gastric cancer (GC). We aim to identify the preparative risk factors for LN metastasis in GC patients. We retrospectively reviewed 424 patients who underwent radical GC resection in our medical center between Jan 2011 and Dec 2018. Multivariate logistic regression was employed to identify risk factors for LN metastasis, while multivariate COX regression was utilized to evaluate prognostic factors. The median overall survival of patients with or without LN metastases was 31 and 58months, respectively. In multivariate analysis, lower albumin (OR = 0.512; P = 0.004) and prealbumin (OR = 0.367, P = 0.001) and higher CEA (OR = 3.178, P < 0.001), CA199 (OR = 2.278, P = 0.002) and platelets (OR = 1.697, P = 0.017) were found to be significantly associated with LN metastasis. In survival analysis, older age (HR = 1.712), larger tumors (HR = 1.082), higher D-dimer (HR = 1.561) and CA199 (HR = 1.553), advanced staging (stage II, HR = 3.446; stage III-IV, HR = 11.089), lower prealbumin levels (lower level for reference, HR = 0.63), and absence of adjuvant chemotherapy (HR = 0.396) was discovered to be associated with poorer overall survival (all P < 0.05). In conclusion, our results demonstrated that preoperative prealbumin-bound tumor markers can effectively predict LN metastasis. Additionally, prealbumin was found to possess prognostic value as well.

Early gastric cancer with RhoGAP fusion is linked to frequent nodal metastasis and a part of microtubular-mucocellular histology.

Gastric cancer with fusion genes involving the Rho GTPase-activating protein domain (RhoGAP-GC) is mainly included in the genomically stable type of The Cancer Genome Atlas classification. Clinical implications and histological characteristics of RhoGAP-GC in the early phase remain unclear. We analyzed 878 consecutive pT1b GCs for RhoGAP and its partner genes using fluorescence in situ hybridization assay. RhoGAP fusion was detected in 57 (6.5%) GCs. Univariate analysis revealed that female sex, middle-lower third tumor location, advanced macroscopic type, tumor diameter > 2cm, pT1b2, lymphatic invasion, venous invasion, negative EBER-ISH, and RhoGAP fusion were significantly associated with lymph node metastasis (LNM). Multivariate analysis presented RhoGAP fusion, lymphatic invasion, tumor diameter > 2cm, advanced macroscopic type, venous invasion, and middle-lower third tumor location as independent risk factors for LNM. Notably, RhoGAP fusion had the highest odds ratio (3.92) for LNM among analyzed parameters (95% CI 2.12-7.27; p < 0.001). Compared to non-RhoGAP-GCs, RhoGAP-GCs were significantly frequent in younger females and showed the highest incidence of lymphatic invasion (56.2%) and LNM (49.1%) (p < 0.001). Histologically, microtubular architecture with pseudo-trabecular interconnection and small aggregations of tumor cells with a varied amount of cytoplasmic mucin, named "microtubular-mucocellular (MTMC) histology," was found in 93.0% (53 of 57) of RhoGAP-GCs in the intramucosal area. MTMC histology showed high sensitivity and negative predictive value (93.0% and 99.4%, respectively) for RhoGAP fusion, albeit positive predictive value is low (34.9%). RhoGAP-GC is linked to a characteristic MTMC histology and a high incidence of LNM.

Clinicopathologic factors correlated with lymph node metastasis in gastric cancer: a retrospective cohort study involving 5606 patients

BackgroundThe identification of risk factors associated with lymph node metastasis (LNM) in gastric cancer will establish a crucial foundation for the implementation of endoscopic operation and multidisciplinary treatment program. Methods5606 gastric cancer patients with comprehensive clinicopathological data were enrolled through systematic searching and rigorous screening. Of the 5606 patients, 1438 were diagnosed with early gastric cancer (EGC), which would be utilized for further analysis. Subsequently, univariate and multivariate logistic regression analyses were conducted to identified the risk factors. ResultsThe rates of LNM in T1a, T1b, T2, T3, T4a, and T4b stage gastric cancer were 7.0%, 19.4%, 48.4%, 77.1%, 83.8%, and 89.6% respectively. Female [odds ratio (OR)=1.559, P=0.032], lower tumor location (OR=1.773, P=0.023), tumor size >2cm (OR=2.007, P<0.001), mixed (OR=2.371, P=0.001) and undifferentiated histological types (OR=2.952, P<0.001), T1b stage (OR=2.041, P<0.001), presence of ulceration (OR=1.758, P=0.027), and lymphovascular invasion (LVI) (OR=5.722, P<0.001) were identified as independent risk factors for LNM in EGC. A nomogram was constructed using appropriate predictors to preoperatively predict the risk of LNM in EGC cases. ConclusionsThis study identified the clinicopathological factors associated with LNM in EGC and developed a prediction model, thereby facilitating the integration of diverse treatment modalities in managing EGC patients.