Evaluating the benefits of adjuvant chemotherapy in patients with pancreatic cancer undergoing radical pancreatectomy after neoadjuvant therapy-a systematic review and meta-analysis.

Background: More and more patients with pancreatic cancer (PC) received neoadjuvant therapy (NAT) and then underwent radical pancreatectomy. However, the benefit of adjuvant chemotherapy (AC) for these patients is still controversial. This study is designed to determine the benefits of postoperative AC for patients with PC undergoing NAT and radical resection. Methods: We conducted a comprehensive search of the PubMed, Embase, Web of Science, and Cochrane Library databases, covering the period from their inception until 10 September 2023. Our analysis focused on the assessment of overall survival (OS) and recurrence-free survival (RFS) through meta-analysis. The fixed-effects model and the random-effects model were used to process the data. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were employed to determine the necessary of administering AC for patients with PC who have undergone NAT and radical resection. We retrieved 3,063 search results, of which 3,048 were excluded because of duplication or after applying our inclusion and exclusion criteria. Results: A total of 15 studies with 21,113 patients (7,794 patients in the AC group and 13,319 in the non-AC group) were included, all of which reported OS, and three studies reported disease-free survival (DFS)/tumor-specific survival (CSS)/RFS. The final results showed that AC significantly improved OS and DFS/CSS/RFS in patients with PC who underwent pancreatectomy after NAT [OS: HR = 0.80, 95% CI (0.75∼0.86), P < 0.00001, I2 = 48%; DFS/CSS/RFS: HR = 0.53, 95% CI (0.41~0.69), P < 0.00001, I2 = 0%]. Furthermore, we performed subgroup analyses and demonstrated that AC provided a significant survival benefit for patients with PC after NAT and resection regardless of the tumor size [<2-cm subgroup: HR = 0.72, 95% CI (0.5∼0.94), P = 0.01; ≥2-cm subgroup: HR = 0.79, 95% CI (0.65∼0.96), P = 0.02] and the margin status [R0 subgroup: HR = 0.83, 95% CI (0.77∼0.88), P < 0.00001; R2 subgroup: HR = 0.75, 95% CI (0.61∼0.92), P = 0.007]. AC also benefited the patients with a stage N0 [HR = 0.79, 95% CI (0.74~0.84), P < 0.00001], N1 [HR = 0.78, 95% CI (0.72∼0.85), P < 0.00001], or poorly/undifferentiated tumor [HR = 0.76, 95% CI (0.66∼0.87), P < 0.0001] in survival but not in patients with a stage N2 [HR = 0.69, 95% CI (0.43∼1.09), P = 0.11] or well/moderately differentiated tumor [HR = 0.97, 95% CI (0.66∼1.42), P = 0.87]. Conclusions: Although AC showed survival benefit for patients with PC undergoing radical pancreatectomy after NAT, we still need to consider the lymph node stage and the degree of differentiation of the tumor when we gave AC to a patient. High-quality prospective randomized controlled studies are required to well disclose the value of AC in patients with PC undergoing radical pancreatectomy after NAT. Systematic review registration: https://www.crd.york.ac.uk/prospero/ PROSPERO, identifier CRD42023461365.

Correlation of inflammatory indices with staging of esophageal carcinoma: A prospective study at Dr. Ruth K. M. Pfau Civil Hospital, Karachi.

Objectives: To determine the correlation between inflammatory indices and the Tumour-Node-Metastasis stage of oesophageal carcinoma. METHODS: The prospective study was conducted from January 2021 to January 2023 at the Department of Upper Gastrointestinal Surgery, Dr Ruth K.M. Pfau Civil Hospital, Karachi, and comprised patients of either gender aged 18- 60 years with biopsy-proven oesophageal cancer. Blood samples were drawn and on the basis of plasma obtained, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, C-reactive protein-to-albumin ratio, lymphocyte-tomonocyte ratio and platelet-to red cell distribution width ratio were calculated. Modified Glasgow Prognostic Score was calculated on the basis of C-reactive protein and albumin levels. Values were compared with tumour length, depth of invasion, lymph node status, vascular involvement, metastasis, pathological subtype and grade of differentiation. Data was analysed using SPSS 24. RESULTS: Of the 220 patients aged 46.1±14.2 years, 120(54%) were females and 100(46%) were males. C-reactive protein-to-albumin ratio demonstrated the highest predictive power for advanced disease stage (p=0.003). Elevated neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio (p=0.010 and p=0.044) were positively correlated with node stage, while elevated platelet-to-lymphocyte ratio was associated with advanced clinical stage (p=0.046). C-reactive protein-to-albumin ratio exhibited positive association with higher tumour stage (p=0.033), node stage (p<0.001) and clinical stage IV (p<0.001). Modified Glasgow Prognostic Score was significantly associated with advanced clinical stage (p<0.001). Conclusion: Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, C-reactive protein-to-albumin ratio, and Modified Glasgow Prognostic Score could be used effectively as a predictor of advanced oesophageal cancer.

Number of involved nodal stations predicts survival in small cell lung cancer.

BACKGROUND: In small cell lung cancer (SCLC), the pathological N category is identical to it in non-small cell lung cancer (NSCLC) and remains unchanged over a decade. Here we verified the discriminability of number of involved nodal stations (nS) in SCLC and compared its efficacy in predicting survival with currently used pathological nodal (pN) staging. METHODS: We retrospectively analyzed the patients who received operations and were pathologically diagnosed as SCLC at Shanghai Pulmonary Hospital between 2009 and 2019. X-tile software was adopted to determine optimal cut-off values for nS groups. Kaplan-Meier method and Cox regression analysis were used to compare survival between different groups. Decision curve analysis (DCA) was employed to evaluate the standardized net benefit. RESULTS: A total of 369 patients were included. The median number of sampled stations was 6 (range 3-11), and the median number of positive stations was 1 (range 0-7). The optimal cutoff for nS groups was: nS0 (no station involved), nS1-2 (one or two stations involved), and nS ≥ 3 (three or more stations involved). Overall survival (OS) and relapse-free survival (RFS) were statistically different among all adjacent categories within the nS classification (p < 0.001, for both OS and RFS between each two subgroups), but survival curves for subgroups in pN overlapped (OS, p = 0.067; RFS, p = 0.068, pN2 vs. pN1). After adjusting for other confounders, nS was a prognostic indicator for OS and RFS. The DCA revealed that nS had improved predictive capability than pN. CONCLUSIONS: Our cohort study demonstrated that the nS might serve as a superior indicator to predict survival than pN in SCLC and was worth considering in the future definition of the N category.

Significance of apparent diffusion coefficient in diagnosis of rectal carcinoma.

Introduction: The apparent diffusion coefficient (ADC) is a quantitative parameter that facilitates the detection and reliable differentiation of rectal cancer. MR differentiation between rectal carcinoma, post-radiation proctitis, and normal rectal wall with the ADC values and their comparison depending on the level of tumor markers and pathohistological characteristics of rectal carcinoma. Methods: The retrospective study performed at the Oncology Institute of Vojvodina included 300 patients, 100 each with rectal cancer, post-radiation proctitis, and normal rectum. Mean ADC values were obtained by measuring the region of interest (ROI) of the rectal wall. Results: Rectal cancer showed lower ADC values (0.665 ± 0.086 x 10-3mm2/s) compared to both post-radiation proctitis (1.648 ± 0.268 x 10-3mm2/s) and normal rectum (1.180 ± 0.110 x 10-3mm2/s) (p<0.001). No significant differences in ADC values were observed between different grades of rectal cancer (p=0.874; p>0.05), depending on the presence of metastases in the lymph nodes (p=0.357; p>0.05), different TN stage (p=0.196; p>0.05), local spread of the tumor (p=0.312; p>0.05), the presence of RAS mutation (p=0.829; p>0.05) and the value of tumor markers (p=0.923; p>0.05). ADC values below 1.013 x 10-3mm2/s with 100% sensitivity and 96% specificity indicate the presence of rectal cancer in relation to normal wall, with a positive predictive value of 96.1% and a negative of 100%. ADC values below 1.255 x 10-3mm2/s with 100% sensitivity and 95% specificity indicate rectal cancer in relation to post-radiation proctitis. ADC values above 1.339 x 10-3mm2/s with 87% sensitivity and 89% specificity indicate post-radiation proctitis in relation to normal wall. Discussion: The ADC is a useful marker in differentiating between rectal cancer, post-radiation proctitis, and normal rectal wall with high sensitivity and specificity, but it cannot be used to distinguish the histological grades of rectal cancer, nor other pathohistological parameters.

Delay in the Diagnosis of Patients With Head and Neck Cancer: Impact of Different Patient- and Healthcare Provider-Related Factors.

Background In our setup, head and neck cancer (HNC) is the most common, and patients frequently present at an advanced stage, which results in dismal outcomes. Delays on the part of the patient (such as resistance to seeking treatment) or the provider (such as misdiagnosis or an extended wait period for consultation) may be the cause of a late presentation. The presentation stage may vary depending on several factors, including age, gender, smoking status, job status, and education. Objectives The study aims to identify factors that lead to advanced-stage presentations of HNCs and to determine the delays brought on by patient- or healthcare provider-related factors and how these factors affect HNC disease staging among biopsy-proven HNC patients. Materials and methods Participants in the study were those who initially presented with a biopsy-verified HNC at the cancer clinic of the department of otolaryngology-head and neck surgery at Pakistan Institute of Medical Sciences (PIMS), Islamabad. Patients answered questions on their first symptom presentation, past healthcare professional visits, and intervals between visits on a Cancer Symptom Interval Measure (C-SIM) questionnaire. For every patient, clinical and demographic information was gathered. TNM staging was completed. The test of significance was applied where applicable. Results Age, gender, education level, and smoking status had no bearing on the presentation stage. Patients without jobs present at a statistically significant higher stage (p = 0.038). The most prevalent histological form of HNC was squamous cell carcinoma 79 (82.29%), with the oral cavity and larynx being the most common sites of the disease 30 (31.25%) and 29 (30.21%) respectively. Patients took an average of 5.28 ± 9.12 months from the onset of symptoms to their first appointment with a healthcare provider. Prior to diagnosis, the majority of patients saw three or more healthcare providers (range: 1-8). The duration from the initial visit to a healthcare provider to the initiation of treatment was 3.06 ± 5.88 months. Based on the stage at presentation, there were no discernible variations in the times to presentation (p>0.05). Conclusion Significant delays and high stage of presentation are caused by unemployment. The majority of the delay was caused by the patient's tardiness in seeing a medical practitioner, yet the presentation stage was not greatly impacted by this delay.

Advanced artificial intelligence framework for T classification of TNM lung cancer in18FDG-PET/CT imaging.

The integration of artificial intelligence (AI) into lung cancer management offers immense potential to revolutionize diagnostic and treatment strategies. The aim is to develop a resilient AI framework capable of two critical tasks: firstly, achieving accurate and automated segmentation of lung tumors and secondly, facilitating the T classification of lung cancer according to the ninth edition of TNM staging 2024 based on PET/CT imaging. This study presents a robust AI framework for the automated segmentation of lung tumors and T classification of lung cancer using PET/CT imaging. The database includes axial DICOM CT and18FDG-PET/CT images. A modified ResNet-50 model was employed for segmentation, achieving high precision and specificity. Reconstructed 3D models of segmented slices enhance tumor boundary visualization, which is essential for treatment planning. The Pulmonary Toolkit facilitated lobe segmentation, providing critical diagnostic insights. Additionally, the segmented images were used as input for the T classification using a CNN ResNet-50 model. Our classification model demonstrated excellent performance, particularly for T1a, T2a, T2b, T3 and T4 tumors, with high precision, F1 scores, and specificity. The T stage is particularly relevant in lung cancer as it determines treatment approaches (surgery, chemotherapy and radiation therapy or supportive care) and prognosis assessment. In fact, for Tis-T2, each increase of one centimeter in tumor size results in a worse prognosis. For locally advanced tumors (T3-T4) and regardless of size, the prognosis is poorer. This AI framework marks a significant advancement in the automation of lung cancer diagnosis and staging, promising improved patient outcomes.

Rethinking the prognosis model of differentiated thyroid carcinoma.

Background: The prediction efficiency of long-term cancer-specific survival (CSS) in guiding the treatment of differentiated thyroid carcinoma (DTC) patients is still unsatisfactory. We need to refine the system so that it more accurately correlates with survival. Methods: This is a retrospective study using the Surveillance, Epidemiology, and End Results (SEER) database, and included patients who underwent surgical treatment and were diagnosed with DTC from 2004 to 2020. Patients were divided into a training cohort (2004-2015) and validation cohort (2016-2020). Decision tree methodology was used to build the model in the training cohort. The newly identified groups were verified in the validation cohort. Results: DTC patient totals of 52,917 and 48,896 were included in the training and validation cohorts, respectively. Decision tree classification of DTC patients consisted of five categorical variables, which in order of importance were as follows: M categories, age, extrathyroidal extension, tumor size, and N categories. Then, we identified five TNM groups with similar within-group CSS. More patients were classified as stage I, and the number of stage IV patients decreased significantly. The new system had a higher proportion of variance explained (PVE) (5.04%) and lower Akaike information criterion (AIC) (18,331.906) than the 8th TNM staging system (a PVE of 4.11% and AIC of 18,692.282). In the validation cohort, the new system also showed better discrimination for survival. Conclusion: The new system for DTC appeared to be more accurate in distinguishing stages according to the risk of mortality and provided more accurate risk stratifications and potential treatment selections.

Exploring the Usefulness of Tumor Budding as a Histopathological Marker Compared to Tumor-Node-Metastasis (TNM) Staging in Breast Cancer.

BACKGROUND:  Tumor budding, defined as small clusters of tumor cells at the invasive front of carcinomas, has gained attention as a potential prognostic marker in various cancers. This study aimed to evaluate the utility of tumor budding as a histopathological marker in breast cancer and compare it to traditional prognostic markers such as histological grading, tumor-node-metastasis (TNM) staging, and molecular subtypes. METHODS:  A prospective, cross-sectional study was conducted over two years (June 2022 to May 2024) in the Department of Pathology at Jawaharlal Nehru Medical College, Wardha. Seventy-two female patients diagnosed with breast carcinoma who underwent modified radical mastectomy were included. Tumor budding was assessed through histopathological analysis and categorized as high or low. Statistical correlations were established between tumor budding and tumor size, histological grade, lymph node involvement, vascular invasion, and molecular subtypes (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and triple-negative breast cancer, TNBC). The chi-square test and multiple regression analyses were applied to assess significance. RESULTS:  High tumor budding was observed in 68.1% of patients and was significantly associated with larger tumor size (p = 0.040), higher histological grade (p = 0.009), lymph node metastasis (p = 0.002), and vascular invasion (p = 0.003). The postmenopausal age group (>55 years) demonstrated a higher prevalence of high budding (p = 0.010). No significant correlation was found between tumor budding and molecular subtypes (p = 0.39), although high budding was more frequent in TNBC cases. CONCLUSION:  Tumor budding is significantly associated with more aggressive tumor characteristics in breast cancer. Incorporating tumor budding into routine pathological assessments alongside TNM staging and histological grading may enhance the ability to identify high-risk patients and guide treatment strategies. Further large-scale, multicenter studies are warranted to confirm its prognostic value.

Software-assisted structured reporting and semi-automated TNM classification for NSCLC staging in a multicenter proof of concept study.

OBJECTIVES: In this multi-center study, we proposed a structured reporting (SR) framework for non-small cell lung cancer (NSCLC) and developed a software-assisted tool to automatically translate image-based findings and annotations into TNM classifications. The aim of this study was to validate the software-assisted SR tool for NSCLC, assess its potential clinical impact in a proof-of-concept study, and evaluate current reporting standards in participating institutions. METHODS: A framework for SR and staging of NSCLC was developed in a multi-center collaboration. SR annotations and descriptions were used to generate semi-automated TNM classification. The SR and TNM classification tools were evaluated by nine radiologists on n = 20 representative [18F]FDG PET/CT studies and compared to the free text reporting (FTR) strategy. Results were compared to a multidisciplinary team reference using a generalized linear mixed model (GLMM). Additionally, participants were surveyed on their experience with SR and TNM classification. RESULTS: Overall, GLMM analysis revealed that readers using SR were 1.707 (CI: 1.137-2.585) times more likely to correctly classify TNM status compared to FTR strategy (p = 0.01) resulting in increased overall TNM correctness in 71.9% (128/178) of cases compared to 62.8% (113/180) FTR. The primary source of variation in classification accuracy was explained by case complexity. Participants rated the potential impact of SR and semi-automated TNM classification as positive across all categories with improved scores after template validation. CONCLUSION: This multi-center study yielded an effective software-assisted SR framework for NSCLC. The SR and semi-automated classification tool improved TNM classification and were perceived as valuable. CRITICAL RELEVANCE STATEMENT: Software-assisted SR provides robust input for semi-automated rule-based TNM classification in non-small-cell lung carcinoma (NSCLC), improves TNM correctness compared to FTR, and was perceived as valuable by radiology physicians. KEY POINTS: SR and TNM classification are underutilized across participating centers for NSCLC staging. Software-assisted SR has emerged as a promising strategy for oncologic assessment. Software-assisted SR facilitates semi-automated TNM classification with improved staging accuracy compared to free-text reports in NSCLC.

Recommendation for Clinical T Staging in Patients with Non-Small Cell Lung Cancer: Volumetric Measurement: A Retrospective Study from Turkey.

Background: Currently, clinical T staging in non-small cell lung cancer (NSCLC) is based on the largest radiological diameter observed on computed tomography (CT). Under this system, tumors with varying shapes-such as spherical, amorphous, or spiculated tumors- can be assigned the same T stage even with different volumes. We aimed to propose a 3-dimensional (3D) volumetric staging system for NSCLC as an alternative to diameter-based T staging and to conduct comparative survival analyses between these methods. Methods: We retrospectively analyzed data from patients who underwent surgery for pT1-4N0M0 primary NSCLC between January 2018 and May 2022. Digital Imaging and Communications in Medicine data from patient CT scans were uploaded to 3D Slicer software for volumetric tumor measurement. Using the paired samples t-test or the Wilcoxon test, we compared the expected tumor volumes, calculated by tumor diameter, with the actual volumes measured by 3D Slicer. Receiver operating characteristic analysis was employed to determine the cut-off value for tumor volume. Kaplan-Meier analysis was utilized to assess overall survival, while the log-rank method was applied to compare survival differences between groups. The significance of changes in T stage was evaluated using the marginal homogeneity test. Results: The study included 136 patients. Significant differences were observed between expected and actual tumor volumes (p=0.01), and associated changes in T stage were also significant (p=0.04). The survival analysis performed using tumor volume (p=0.009) yielded superior results compared to that based on diameter (p=0.04) in paients with early tumor stage. Conclusion: T-factor staging based on tumor volume could represent an alternative staging method for NSCLC.

Outcome Disparities in Patients with Early-Stage Laryngeal Cancer Depending on Localization, Tobacco Consumption, and Treatment Modality.

Background/Objectives: Laryngeal squamous cell carcinoma (LSCC) is among most frequent malignancies of the head and neck. Recent oncologic research focusses on advanced rather than on early stages. Thus, we aimed to improve the knowledge concerning prognostic factors and survival in early glottic (GC) and supraglottic cancer (SGC). Methods: We retrospectively investigated patients diagnosed in 2007 to 2020 with stage I or II GC (ICD-10-C32.0) or SGC (ICD-10-C32.1, C32.8 or C32.9). For precise discrimination of GC and SGC, pathology reports about biopsy and definitive excision were closely examined and information on clinical characteristics and risk factors were collected before analyzing patterns of risk factors for overall survival (OS) in multivariate Cox regression analyses (mvCox). Results: The cohort included 220 patients with early GC (n = 183) and SGC (n = 37). The GC patients showed significantly improved 5-year OS compared to SGC patients (83.6% vs. 64.9%; p = 0.004), whereas survival according to UICC stage (I vs. II) was not different (p = 0.177). Surgical resection was superior to definitive radiotherapy (RT) for 5-year OS (p < 0.001). Cumulative tobacco consumption of greater than 10 pack years drastically impaired OS (p = 0.024), especially in patients receiving RT (p < 0.001). Supraglottic localization, smoking, and re-resection after initial R1 status consistently were independent prognostic factors in mvCox. Conclusions: Our cohort of early LSCC patients demonstrates significant negative impact of supraglottic localization, older age, tobacco consumption, poor tumor differentiation, and re-resection on OS. Further research is required as there is still lack of evidence on optimal decision-making and therapeutic strategies.

The Role of Risk Factors for the Progression of Patients with T1b-T2 Papillary Thyroid Carcinoma (PC) during Long-Term Follow-Up.

Background/Objectives: Recurrence prediction for patients with PC and tumor sizes ranging between 1 and 4 cm, classified as T1b and T2, remains a controversial problem. We evaluated which risk factors, identified during the primary tumor surgery, might play a prognostic role in predicting disease progression. Methods: We retrospectively enrolled 363 patients with classic PC who were in follow-up (207 T1b, 156 T2), with tissue risk factors at surgery in 209/363 cases. In all cases, an 131I-whole-body scan, SPECT/CT, and US were employed to detect any metastases during follow-up, and histology was used to confirm lesions. In the absence of surgery, metastases were validated by radioisotopic and radiologic procedures, eventually culminating in a needle biopsy and sequential thyroglobulin changes. Results: Metastases occurred in 61/363 (16.8%) patients (24 T1b, 37 T2). In 50/61 cases, the following risk factors were identified: minimal extrathyroid tumor extension (mETE) alone in 12/50 patients, neck lymph node (LN) metastases in 8/50 cases, and multifocality/multicentricity (M/M) in 6/50 cases. In the remaining 24/50 cases, the risk factors were associated with each other. From a Cox regression multivariate analysis, metastasis development was significantly (p < 0.001) influenced by only mETE and LN metastases, with a shorter disease-free survival (log-rank test). Conclusions: The current study proves that mETE and neck LN metastases are associated with aggressive PC. While LN metastasis' role is known, mETE's role is still being debated, and was removed by the AJCC's eighth edition because it was considered to not be associated with an unfavorable prognosis. However, this interpretation is not supported by the present study and, according to comparable studies, we suggest a revision of the mETE classification be considered in the next AJCC edition.

A prospective study to compare the diagnostic accuracy of 99mTc-CNDG SPECT/CT and contrast-enhanced CT in staging of non-small cell lung cancer.

OBJECTIVE: To explore the value of 99mTc-isonitrile deoxyglucosamine (CNDG) SPECT/CT in the staging and resectability diagnosis of non-small cell lung cancer (NSCLC) compared with contrast-enhanced CT (CECT). METHODS: This research was approved by the hospital ethics review committee. Sixty-three patients with NSCLC received 99mTc-CNDG SPECT/CT, CECT and initial TNM staging before treatment. Thirty-three patients who underwent radical surgery underwent postoperative pathological TNM staging as the reference standard. Another thirty patients underwent radiochemotherapy; among them, the reference standard of 7 patients of N staging and 5 patients of M staging was based on biopsy pathology, and the diagnosis of the remaining lesions was confirmed by at least one different image or clinical imaging follow-up for more than 3 months. The McNemar test and receiver operating characteristic (ROC) curve analysis were used to compare the diagnostic accuracy of staging and resectability of 99mTc-CNDG SPECT/CT and CECT in NSCLC, respectively. RESULTS: For all patients and surgical patients, the accuracies of 99mTc-CNDG SPECT/CT in diagnosing the T stage and N stage were higher than those of CECT (all patients: 90.5%, 88.9% vs. 79.4%, 60.3%; surgical patients: 81.8%, 78.8% vs. 60.6%, 51.5%), and the differences were statistically significant (all patients: T stage, P = 0.016; N stage, P = 0.000; surgical patients: T stage, P = 0.016; N stage, P = 0.004). For all patients, the accuracy of 99mTc-CNDG SPECT/CT in diagnosing the M stage was higher than that of CECT (96.8% vs. 90.5%), but the difference was not statistically significant (P = 0.289). ROC curve analysis showed that the accuracy of 99mTc-CNDG SPECT/CT in diagnosing the potential resectability of NSCLC was significantly better than that of CECT (P = 0.046). CONCLUSION: This preliminary clinical study shows that 99mTc-CNDG SPECT/CT is of great value for accurate clinical staging of NSCLC compared with CECT and can significantly improve the accuracy of resectability diagnosis.

Exploring Individualized Follow-up of Gastric Cancer After Radical Surgery Based on pTNM Stage: A Retrospective Cohort Study From China.

Background: Patients with gastric cancer (GC) who underwent radical surgery require long-term follow-up (usually 5 years). The purpose of this study was to explore individualized follow-up strategies for patients with GC. Methods: This is a retrospective cohort study that established a clinicopathologic database of patients who underwent gastrectomy from January 2010 to December 2020 at Ningbo No. 2 Hospital. Follow-up was performed until March 2023. The rate of new-onset recurrence of patients with GC was explored annually according to different pTNM stages, defining a recurrence rate of less than 1% as adequate follow-up time. Results: Of the 1606 patients who were eligible, the total number of patients who completed the 5- and 10-year follow-up was 1107 and 586, respectively. A total of 444 cases were diagnosed with recurrence. The recurrence rate for stage IA patients was consistently less than 1% during the follow-up time. The adequate follow-up time (the rate of new-onset recurrence less than 1%) was 5 years for stage IB and IIA patients, and 8 years for stage IIB and IIIA patients, respectively. In contrast, stage IIIB patients were always at risk of recurrence during the follow-up time (>1%). Time to a new recurrence rate for stage IIIC patients was 6 years. Conclusion: Among patients who underwent radical gastrectomy, the rate of new-onset recurrence varied among patients with different pTNM stages. This study suggests that the follow-up of GC can be individualized and refer to pTNM stage.

The prognostic impact of tumor deposits in colorectal cancer: More than just N1c.

BACKGROUND: The identification of tumor deposits (TD) currently plays a limited role in staging for colorectal cancer (CRC) aside from N1c lymph node designation. The objective of this study was to determine the prognostic impact, beyond American Joint Committee on Cancer N1c designation, of TDs among patients with primary CRC. METHODS: Patients who had resected stage I-III primary CRC diagnosed between 2010 and 2019 were identified from the National Cancer Institute's Surveillance, Epidemiology, and End Results database. Cancer-specific survival (CSS) stratified by TD status and lymph node (N) status was calculated using the Kaplan-Meier method and multivariable Cox proportional hazards regression analyses. RESULTS: In total, 147,783 patients with primary CRC were identified. TDs were present in 15,444 patients (10.5%). The presence of TDs was significantly associated with adverse tumor characteristics, including advanced pathologic stage, nodal status, and metastasis status. The presence of TDs was associated with worse CSS (hazard ratio [HR], 3.12; 95% confidence interval [CI], 3.02-3.22), as it was for each given N category (e.g., N2a and TD-negative [HR, 2.50; 95% CI, 2.37-2.64] vs. N2a and TD-positive [HR, 3.75; 95% CI, 3.49-4.03]). The presence of multiple TDs was also associated with decreased CSS for each given N category compared with a single TD (e.g. N2a with one TD [HR, 3.09; 95% CI, 2.65-3.61] vs. N2a with two or more TDs [HR, 4.32; 95% CI, 3.87-4.82]). CONCLUSIONS: TDs were identified as an independent predictor of a worse outcome in patients with CRC. The presence of TDs confers distinctly different CSS and provides important prognostic information among patients with CRC and warrants further investigation as a unique variable in future iterations of CRC staging.

To study the utility of HER2 and Ki-67 as immunohistochemical prognostic markers in comparison to histopathological parameters and tumour, node and metastasis staging in colorectal carcinoma.

Colorectal Carcinoma (CRC) ranks among the most prevalent cancers globally, with significant variability in incidence rates across different regions. A shift towards a Westernized diet has been implicated in rising cancer rates, particularly in emerging nations. By 2020, CRC is projected to represent a notable proportion of global cancer cases and deaths. In India, CRC primarily affects individuals aged 45 to 84, with a higher incidence in males, commonly occurring in the rectum and sigmoid colon. Risk factors such as obesity, dietary factors, sedentary lifestyle, smoking, and alcohol use contribute to CRC development, especially in aging populations. Diagnosis involves various imaging modalities and histological assessments using Tumour, node and metastasis (TNM) and American Joint Committee on Cancer classifications. Recent advancements in targeted therapies like monoclonal antibodies against HER2 have shown promise in treating metastatic CRC. Immunohistochemistry markers like Ki-67 and HER2 play crucial roles in prognostic assessment and treatment planning. This study aims to investigate Ki-67 and HER2 expression in CRC, correlating with histological characteristics and prognostic factors.

The prognosis and metabolite changes of NSCLC patients receiving first-line immunotherapy combined chemotherapy in different M1c categories according to 9th edition of TNM classification.

BACKGROUND: The 9th edition of the TNM Classification for lung cancer delineates M1c into two subcategories: M1c1 (Multiple extrathoracic lesions within a single organ system) and M1c2 (Multiple extrathoracic lesions involving multiple organ systems). Existing research indicates that patients with lung cancer in stage M1c1 exhibit superior overall survival compared to those in stage M1c2. The primary frontline therapy for patients with advanced non-small cell lung cancer (NSCLC), lacking driver gene mutations, involves the use of immune checkpoint inhibitors (ICIs) combined with chemotherapy. Nevertheless, a dearth of evidence exists regarding potential survival disparities between NSCLC patients with M1c1 and M1c2 undergoing first-line immune-chemotherapy, and reliable biomarkers for predicting treatment outcomes are elusive. Serum metabolic profiles may elucidate distinct prognostic mechanisms, necessitating the identification of divergent metabolites in M1c1 and M1c2 undergoing combination therapy. This study seeks to scrutinize survival discrepancies between various metastatic patterns (M1c1 and M1c2) and pinpoint metabolites associated with treatment outcomes in NSCLC patients undergoing first-line ICIs combined with chemotherapy. METHOD: In this study, 33 NSCLC patients lacking driver gene mutations diagnosed with M1c1, and 22 similarly diagnosed with M1c2 according to the 9th edition of TNM Classification, were enrolled. These patients received first-line PD-1 inhibitor plus chemotherapy. The relationship between metastatic patterns and progression-free survival (PFS) in patients undergoing combination therapy was analyzed using univariate and multivariate Cox regression models. Serum samples were obtained from all patients before treatment initiation for untargeted metabolomics analysis, aiming to identify differential metabolites. RESULTS: In the univariate analysis of PFS, NSCLC patients in M1c1 receiving first-line PD-1 inhibitor plus chemotherapy exhibited an extended PFS (HR = 0.49, 95% CI, 0.27-0.88, p = 0.017). In multivariate PFS analyses, these M1c1 patients receiving first-line PD-1 inhibitor plus chemotherapy also demonstrated prolonged PFS (HR = 0.45, 95% CI, 0.22-0.92, p = 0.028). The serum metabolic profiles of M1c1 and M1c2 undergoing first-line PD-1 inhibitors plus chemotherapy displayed notable distinctions. In comparison to M1c1 patients, M1c2 patients exhibited alterations in various pathways pretreatment, including platelet activation, linoleic acid metabolism, and the VEGF signaling pathway. Diminished levels of lipid-associated metabolites (diacylglycerol, sphingomyelin) were correlated with adverse outcomes. CONCLUSION: NSCLC patients in M1c1, devoid of driver gene mutations, receiving first-line PD-1 inhibitors combined with chemotherapy, experienced superior outcomes compared to M1c2 patients. Moreover, metabolomic profiles strongly correlated with the prognosis of these patients, and M1c2 patients with unfavorable outcomes manifested distinct changes in metabolic pathways before treatment. These changes predominantly involved alterations in lipid metabolism, such as decreased diacylglycerol and sphingomyelin, which may impact tumor migration and invasion.

Tumor deposits should not be placed in the M category of TNM: A comparative survival analysis using SEER data.

Tumor deposits (TD) are tumor nodules in the lymphatic drainage area of colorectal cancer patients, and they are currently classified in the N category in the TNM classification. However, due to the associated poor prognosis, some small cohort studies suggest that TD belong in the M category. A retrospective study using The Surveillance, Epidemiology, and End Results program (SEER) data was performed in Stages III and IV colon carcinoma (CC) patients to evaluate the prognostic impact of TD. In multivariate analysis, TD have significantly negative effect on survival in both stages (Stage III HR = 1.4 [95% CI 1.4-1.5] and Stage IV HR = 1.3 [95% CI 1.2-1.3]). In Stage III, 5-year overall survival (OS) for patients with TD 49%, whereas it was 64% for patients without TD (p < .001). Additionally, in Stage IV patients without TD, the 5-year OS rates are superior at 21% compared to patients with TD, who show 5-year OS rate of 10% (p < .001). Stage III patients with TD (5-year OS 49%) have a significantly better prognosis compared to Stage IV patients (5-year OS 17%, p < .001). Therefore, despite the previous suggestions, this large scale study (n = 52,332) on outcomes in CC does not support the classification of TD in Stage IV.