Predictor Of Disease-free Survival Research Articles

Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer

Prognostic markers currently utilized in clinical practice for estrogen receptor-positive (ER+) and lymph node-negative (LN−) invasive breast cancer (IBC) patients include the Nottingham grading system and Oncotype Dx (ODx). However, these biomarkers are not always optimal and remain subject to inter-/intra-observer variability and high cost. In this study, we evaluated the association between computationally derived image features from H&E images and disease-free survival (DFS) in ER+ and LN− IBC. H&E images from a total of n = 321 patients with ER+ and LN− IBC from three cohorts were employed for this study (Training set: D1 (n = 116), Validation sets: D2 (n = 121) and D3 (n = 84)). A total of 343 features relating to nuclear morphology, mitotic activity, and tubule formation were computationally extracted from each slide image. A Cox regression model (IbRiS) was trained to identify significant predictors of DFS and predict a high/low-risk category using D1 and was validated on independent testing sets D2 and D3 as well as within each ODx risk category. IbRiS was significantly prognostic of DFS with a hazard ratio (HR) of 2.33 (95% confidence interval (95% CI) = 1.02–5.32, p = 0.045) on D2 and a HR of 2.94 (95% CI = 1.18–7.35, p = 0.0208) on D3. In addition, IbRiS yielded significant risk stratification within high ODx risk categories (D1 + D2: HR = 10.35, 95% CI = 1.20–89.18, p = 0.0106; D1: p = 0.0238; D2: p = 0.0389), potentially providing more granular risk stratification than offered by ODx alone.

Evaluation the benefits of additional radiotherapy for gastric cancer patients after D2 resection using CT based radiomics.

The value of adding radiotherapy (RT) is still unclear for patients with gastric cancer (GC) after D2 lymphadenectomy. The purpose of this study is to predict and compare the overall survival (OS) and disease-free survival (DFS) of GC patients treated by chemotherapy and chemoradiation based on contrast-enhanced CT (CECT) radiomics. A total of 154 patients treated by chemotherapy and chemoradiation in authors' hospital were retrospectively reviewed and randomly divided into the training and testing cohorts (7:3). Radiomics features were extracted from contoured tumor volumes in CECT using the pyradiomics software. Radiomics score and nomogram with integrated clinical factors were developed to predict the OS and DFS and evaluated with Harrell's Consistency Index (C-index). Radiomics score achieved a C index of 0.721(95%CI: 0.681-0.761) and 0.774 (95%CI: 0.738-0.810) in the prediction of DFS and OS for GC patients treated by chemotherapy and chemoradiation, respectively. The benefits of additional RT only demonstrated in subgroup of GC patients with Lauren intestinal type and perineural invasion (PNI). Integrating clinical factors further improved the prediction ability of radiomics models with a C-index of 0.773 (95%CI: 0.736-0.810) and 0.802 (95%CI: 0.765-0.839) for DFS and OS, respectively. CECT based radiomics is feasible to predict the OS and DFS for GC patients underwent chemotherapy and chemoradiation after D2 resection. The benefits of additional RT only observed in GC patients with intestinal cancer and PNI.

18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy.

We investigated whether baseline [18F] Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each 18F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline 18F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.

Programmed death ligand 1 expression in diffuse large B cell lymphoma: correlation with clinicopathological prognostic factors

BackgroundThe prognostic value of the level of programmed death ligand 1 (PD-L1) expression in non-Hodgkin lymphoma (NHL) is still debatable. This study examined the effect of the level of PD-L1 expression on the clinicopathological characteristics and prognosis of diffuse large B cell lymphoma (DLBCL).MethodsA retrospective study was conducted on formalin-fixed paraffin-embedded tissue blocks of one hundred de novo DLBCL patients diagnosed from 2013 to 2016. PD-L1 expression was defined by a modified Combined-Positive Score (CPS) and their medical records were reviewed to collect their clinical, laboratory and radiological data, treatment, and outcome.ResultsThe included patients were aged from 23 to 85 years and treated by rituximab- cyclophosphamide, doxorubicin, oncovin, prednisone (R-CHOP); 49% were males; 85% of the cases were presented at Ann Arbor stages III, IV; 33% of patients were seropositive for HCV and 87% of cases were presented with intermediate and high IPI. All included cases expressed PD-L1 using modified CPS. 27% of patients showed low PD-L1 expression (≥ 5% to < 50% of total tumor cellularity) while 73% of patients showed high PD-L1expression (≥ 50% of total tumor cellularity). High PD-L1 expression is statistically correlated with advanced stage (p 0.01), high IPI score (p 0.017), high incidence of stationary and progressive disease (p 0.002) and high incidence of relapse (p value 0.01). Five-year disease-free survival (DFS) was 29% for patients with high PD-L1 expression compared with 84.8% for patients with low PD-L1 expression (p 0.001).ConclusionsThis study suggests that high PD-L1 expression in DLBCL is associated with aggressive clinicopathological features and a decreased response to R-CHOP. The level of PD-L1 expression could be an independent predictor of DFS of DLBCL. More research is mandatory to standardize the cutoff value and scoring methods.

Specific human leukocyte antigen class I genotypes predict prognosis in resected pancreatic adenocarcinoma: a retrospective cohort study.

Patients with resected pancreatic adenocarcinoma (PAAD) often experience short-term relapse and dismal survival, suggesting an urgent need to develop predictive and/or prognostic biomarkers for these populations. Given the potential associations of the human leukocyte antigen class I ( HLA -I) genotype with oncogenic mutational profile and immunotherapy efficacy, we aimed to assess whether differential HLA -I genotype could predict the postoperative outcomes in resected PAAD patients. HLA -I ( A , B , and C ) genotyping and somatic variants of 608 Chinese PAAD patients were determined by targeted next-generation sequencing of matched blood cells and tumor tissues. HLA - A / B alleles were classified with the available definition of 12 supertypes. The Kaplan-Meier curves of disease-free survival (DFS) and multivariable Cox proportional-hazards regression analyses were performed to determine the survival difference in 226 selected patients with radical resection. Early-stage (I-II) patients constituted the majority (82%, 185/226) and some stage I-II individuals with high-quality tumor samples were analyzed by RNA-sequencing to examine immunophenotypes. Patients with HLA-A02 + B62 + B44 - had significantly shorter DFS (median, 239 vs. 410 days; hazard ratio=1.65, P =0.0189) than patients without this genotype. Notably, stage I-II patients carrying HLA-A02 + B62 + B44 - had sharply shorter DFS than those without HLA-A02 + B62 + B44 - (median, 237 vs. 427 days; hazard ratio=1.85, P =0.007). Multivariate analysis revealed that HLA-A02 + B62 + B44 - was associated with significantly inferior DFS ( P =0.014) in stage I-II patients but not in stage III patients. Mechanistically, HLA-A02 + B62 + B44 - patients were associated with a high rate of KRAS G12D and TP53 mutations, lower HLA-A expression, and less inflamed T-cell infiltration. The current results suggest that a specific combination of germline HLA-A02/B62/B44 supertype, HLA-A02 + B62 + B44 - , was a potential predictor for DFS in early-stage PAAD patients after surgery.

Prognostic effect of CD73 in pancreatic ductal adenocarcinoma for disease-free survival after radical surgery.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease with a high potency of metastasis or recurrence after radical resection. Effective predictors for metastasis and recurrence postoperatively were dominant for the development of systemic adjuvant treatment regimens. The ATP hydrolase correlated gene CD73 was described as a promoter in tumor growth and immune escape of PDAC. However, there lacked research focused on the role of CD73 in PDAC metastasis. This study aimed to investigate the expression of CD73 in PDAC patients with different outcomes as well as the prognostic effect of CD73 for disease-free survival (DFS). The expression level of CD73 in cancerous samples from 301 PDAC patients was evaluated by immunohistochemistry (IHC) and translated into a histochemistry score (H-score) by the HALO analysis system. Then, the CD73 H-score was involved in multivariate Cox regression along with other clinicopathological characteristics to find independent prognostic factors for DFS. Finally, a nomogram was constructed based on those independent prognostic factors for DFS prediction. Higher CD73 expression was found in PDAC patients with tumor metastasis postoperatively. Meanwhile, higher CD73 expressions were also investigated in PDAC patients diagnosed with advanced N stage and T stage. Furthermore, CD73 H-score along with tumor margin status, CA19-9, 8th N stage, and adjuvant chemotherapy was indicated as independent prognostic factors for DFS in PDAC patients. The nomogram based on these factors predicted DFS in a good manner. CD73 was associated with PDAC metastasis and served as an effective prognostic factor for DFS in PDAC patients after radical surgery.

Changing trends, clinicopathological characteristics, surgical treatment patterns, and prognosis of schistosomiasis-associated versus non-schistosomiasis-associated colorectal cancer: a large retrospective cohort study of 31153 cases in Shanghai, China (2001-2021).

With the elimination of schistosomiasis in China, its role in the pathogenesis of colorectal cancer (CRC) has decreased. However, the trends, clinicopathological features, surgical treatment patterns, and prognosis of schistosomiasis-associated CRC (SACRC) versus non-schistosomiasis-associated CRC (NSACRC) in China remain unclear. The percentage trend of SACRC in CRC patients in China was analyzed using data retrieved from the Pathology Registry of Changhai Hospital (2001-2021). Clinicopathological characteristics, surgical treatment patterns, and prognosis-related parameters were compared between the two groups. Multivariate Cox regression analyses were performed for disease-free survival (DFS) and overall survival (OS). A total of 31153 CRC cases were included, with 823 (2.6%) cases of SACRC and 30330 (97.4%) cases of NSACRC. The average percentage of SACRC cases has decreased continuously from 3.8 to 1.7% (from 2001 to 2021). Compared with the NSACRC group, the SACRC group had more men, older age at diagnosis, lower BMI, fewer symptoms; higher rates of rectal cancer, comorbidities, KRAS mutation, multiple primary CRC and concomitant polyps; less lymph node metastasis, distant metastasis, vascular invasion, and tumor budding; less preoperative radiotherapy and preoperative chemotherapy; and more positive resection margins and postoperative targeted therapy. There were no significant differences between the two groups regarding laparoscopic surgery, palliative resection, extended radical resection, or ostomy. Moreover, the SACRC group had adverse DFS and similar OS compared with the NSACRC group. In multivariate analyses, schistosomiasis was not an independent predictor of DFS or OS. The percentage of SACRC in CRC (2.6%) in our hospital was very low, and it decreased continuously over the last two decades, indicating that schistosomiasis is no longer an important risk factor for CRC in Shanghai, China. Patients with SACRC have distinct clinicopathological, molecular, and treatment-related features and survival rates similar to those with NSACRC.

Predicting the recurrence and overall survival of patients with glioma based on histopathological images using deep learning.

A deep learning (DL) model based on representative biopsy tissues can predict the recurrence and overall survival of patients with glioma, leading to optimized personalized medicine. This research aimed to develop a DL model based on hematoxylin-eosin (HE) stained pathological images and verify its diagnostic accuracy. Our study retrospectively collected 162 patients with glioma and randomly divided them into a training set (n = 113) and a validation set (n = 49) to build a DL model. The HE-stained slide was segmented into a size of 180 × 180 pixels without overlapping. The patch-level features were extracted by the pre-trained ResNet50 to predict the recurrence and overall survival. Additionally, a light-strategy was introduced where low-size digital biopsy images with clinical information were inputted into the DL model to ensure minimum memory occupation. Our study extracted 512 histopathological features from the HE-stained slides of each glioma patient. We identified 36 and 18 features as significantly related to disease-free survival (DFS) and overall survival (OS), respectively, (P < 0.05) using the univariate Cox proportional-hazards model. Pathomics signature showed a C-index of 0.630 and 0.652 for DFS and OS prediction, respectively. The time-dependent receiver operating characteristic (ROC) curves, along with nomograms, were used to assess the diagnostic accuracy at a fixed time point. In the validation set (n = 49), the area under the curve (AUC) in the 1- and 2-year DFS was 0.955 and 0.904, respectively, and the 2-, 3-, and 5-year OS were 0.969, 0.955, and 0.960, respectively. We stratified the patients into low- and high-risk groups using the median hazard score (0.083 for DFS and-0.177 for OS) and showed significant differences between these groups (P < 0.001). Our results demonstrated that the DL model based on the HE-stained slides showed the predictability of recurrence and survival in patients with glioma. The results can be used to assist oncologists in selecting the optimal treatment strategy in clinical practice.

Radiological lymph-node size improves the prognostic value of systemic inflammation index in rectal cancer with pathologically negative nodes.

The relationship between the radiological lymph node (rLN) size and survival outcome in node-negative rectal cancer is still uncertain. In this study, we aimed to explore the role of enlarged rLN in predicting the survival of node-negative rectal cancers. We retrospectively reviewed the records of 722 node-negative rectal cancer who underwent curative resection. Factors associated with DFS (disease-free survival) and CSS (cancer-specific survival) were assessed with univariate and multivariate analysis. Survival analysis was performed according to presence with or without enlarged rLN. Combining rLN with NLR as a new index-inflammation immune score (IIS) for predicting survival. Comparing different models to assess the predictive powers. A total of 119 patients had tumor recurrence and 73 patients died due to cancer. Patients with enlarged rLN (≥5 mm) was significantly associated with better DFS (HR:0.517, 95%CI:0.339-0.787, p=0.002) and CSS (HR:0.43, 95%CI:0.242-0.763, p=0.004). The risk factors of recurrence were rLN, neutrophil-lymphocyte ratio (NLR), CEA level, and distance from the anal verge. The risk of recurrence increased by 1.88- and 2.83-fold for the high score in IIS compared with the low and intermediate score group (All p < 0.001). Similarly, the high score in IIS also increased the risk of cancer-specific death. In the model comparison, the AIC and LR were improved by including the rLN into the NLR model for DFS and CSS prediction (All p < 0.05). Node-negative rectal cancer patients with enlarged rLN had a better survival outcome. IIS might be a more comprehensive and complete inflammation immune index for survival prediction.

Value of lymph node ratio as a prognostic factor of recurrence in medullary thyroid cancer.

The purpose of this study is to evaluate the relationship between lymph node status (the number of resected lymph nodes; the number of metastatic lymph nodes, LNM, and lymph node ratio, LNR) and biochemical recurrence, disease-free survival (DFS), as well as overall survival (OS) in medullary thyroid carcinoma (MTC). This study enrolled MTC patients at Tianjin Medical University Cancer Institute and Hospital between 2011 and 2019. We used Logistic regression analysis, Cox regression models and Kaplan-Meier test to identify risk factors influencing biochemical recurrence, DFS, and OS. We identified 160 patients who satisfied the inclusion criteria from 2011 to 2019. We used ROC analysis to define the cut-off value of LNR with 0.24. Multifocality, preoperative calcitonin levels, pathologic N stage, resected lymph nodes, LNM, LNR, and the American Joint Committee on Cancer (AJCC) clinical stage were significant (P < 0.05) prognostic factors influencing biochemical cure. In univariable analyses, gross extrathyroidal extension, preoperative calcitonin levels, pathologic T classification, pathologic N stage, resected lymph nodes, LNM, LNR, AJCC clinical stage, and biochemical cure were significant (P < 0.05) factors of DFS. When the multivariable analysis was performed, LNR was identified as predictor of DFS (HR = 4.818, 95% CI [1.270-18.276]). Univariable Cox regression models reflected that tumor size, pathologic N stage, and LNR were predictor of OS. Furthermore, multivariable analysis manifested that LNR was predictor of OS (HR = 10.061, 95% CI [1.222-82.841]). This study illustrated that LNR was independent prognostic factor of DFS and OS in MTC. In addition, LNR influenced biochemical cure. Further investigations are needed to determine the optimal cut-off value for predicting prognosis.

Prognostic value of the immunohistochemical score based on four markers in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) ranks sixth among all cancers globally regarding morbidity, and it has a poor prognosis, high mortality, and highly aggressive properties. In this study, we established a model for predicting prognosis based on immunohistochemical (IHC) scores. Data on 402 HNSCC cases were collected, the glmnet Cox proportional hazards model was used, risk factors were analyzed for predicting the prognosis of survival, and the IHC score was established. We used the IHC score to predict disease-free survival (DFS) using training and independent validation cohorts, including 264 cases in total. Additionally, the accuracy of the IHC score and the TNM system (8th edition) was compared. A DFS prediction nomogram was established by combining the prognostic factors. The IHC scores included CK, Ki-67, p16, and p40 staining intensity. The concordance index and the Kaplan-Meier survival analysis showed that the IHC scores had high predictive power for HNSCC. Our results showed that the IHC score is an independent factor that can predict prognosis in a multivariate Cox regression analysis. When predicting DFS, the IHC score had a significantly higher value for the area under the ROC curve (AUC) than that of the TNM system. A nomogram was established and included the IHC score, age, tumor location, and the TNM stage. The calibration curves exhibited high consistency between the prognosis predicted by our nomogram and the actual prognosis. The IHC score was more accurate than the eighth edition of the TNM system in predicting HNSCC prognosis. Therefore, combining the two methods can facilitate individualized patient consultation and care.

Prognostic analysis of three forms of Ki-67 in patients with breast cancer with non-pathological complete response before and after neoadjuvant systemic treatment.

Patients who do not achieve a pathological complete response (pCR) after neoadjuvant systemic treatment (NST) have a significantly worse prognosis. A reliable predictor of prognosis is required to further subdivide non-pCR patients. To date, the prognostic role in terms of disease-free survival (DFS) between the terminal index of Ki-67 after surgery (Ki-67T ) and the combination of the baseline Ki-67 at biopsy before NST (Ki-67B ) and the percentage change in Ki-67 before and after NST (Ki-67C ) has not been compared. This study aimed to explore the most useful form or combination of Ki-67 that can provide prognostic information to non-pCR patients. We retrospectively reviewed 499 patients who were diagnosed with inoperable breast cancer between August 2013 and December 2020 and received NST with anthracycline plus taxane. Among all the patients, 335 did not achieve pCR (with a follow-up period of ≥1year). The median follow-up duration was 36 months. The optimal cutoff value of Ki-67C to predict a DFS was 30%. A significantly worse DFS was observed in patients with a low Ki-67C (p < 0.001). In addition, the exploratory subgroup analysis showed relatively good internal consistency. Ki-67C and Ki-67T were considered as independent risk factors for DFS (both p < 0.001). The forecasting model combining Ki-67B and Ki-67C showed a significantly higher area under the curve at years 3 and 5 than Ki-67T (p=0.029 and p=0.022, respectively). Ki-67C and Ki-67T were good independent predictors of DFS, whereas Ki-67B was a slightly inferior predictor. The combination of Ki-67B and Ki-67C is superior to Ki-67T for predicting DFS, especially at longer follow-ups. Regarding clinical application, this combination could be used as a novel indicator for predicting DFS to more clearly identify high-risk patients.

Predictive value of modified MRI-based split scar sign (mrSSS) score for pathological complete response after neoadjuvant chemoradiotherapy for patients with rectal cancer.

To measure the diagnostic performance of modified MRI-based split scar sign (mrSSS) score for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for patients with rectal cancer. The modified MRI-based split scar sign (mrSSS) score, which consists of T2-weighted images (T2WI)-based score and diffusion-weighted images (DWI)-based score. The sensitivity, specificity, and accuracy of modified mrSSS score, endoscopic gross type, and MRI-based tumor regression grading (mrTRG) score, in the prediction of pCR, were compared. The prognostic value of the modified mrSSS score was also studied. A total of 189 patients were included in the study. The Kendall's coefficient of interobserver concordance of modified mrSSS score, T2WI -based score, and DWI-based score were 0.899, 0.890, and 0.789 respectively. And the maximum and minimum k value of the modified mrSSS score was 0.797 (0.742-0.853) and 0.562 (0.490-0.634). The sensitivity, specificity, and accuracy of prediction of pCR were 0.66, 0.97, and 0.90 for modified mrSSS score; 0.37, 0.89, and 0.78 for endoscopic gross type (scar); and 0.24, 0.92, and 0.77 for mrTRG score (mrTRG = 1). The modified mrSSS score had significantly higher sensitivity than the endoscopic gross type and the mrTRG score in predicting pCR. Patients with lower modified mrSSS scores had significantly longer disease-free survival (P < 0.05). The modified mrSSS score showed satisfactory interobserver agreement and higher sensitivity in predicting pCR after nCRT in patients with rectal cancer. The modified mrSSS score is also a predictor of disease-free survival.

Prognostic role of platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte, and lymphocyte-to-monocyte ratio in operated rectal cancer patients: systematic review and meta-analysis.

Inflammation plays an important role in tumor growth. Novel serum blood biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR), have been proposed as useful prognostic indexes in cancer patients. However, their role in rectal cancer is controversial. A comprehensive literature review was conducted including MEDLINE/Pubmed, EMBASE, SCOPUS, and the Cochrane Database of Systematic Reviews through May 2022. The systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Quality was appraised with the Methodological Index for Non-Randomized Studies (MINORS) tool. Aim of the study was to summarize available literature on PLR, NLR, and LMR in patients with rectal cancer undergoing resection. Forty-seven observational studies (14,205 patients) were included; there were 42 retrospective and 5 prospective cohort studies with an average MINORS score of 14.6 (range: 12-18). Worse overall survival was associated with high NLR (HR 1.81; 95%CI 1.52-2.15; p < 0.001), high PLR (HR 1.24; 95%CI 1.06-1.46; p = 0.009), and low LMR (HR 0.67; 95%CI 0.49-0.91; p = 0.01). High NLR and low LMR were also associated with disease-free-survival (HR 1.68; 95%CI 1.35-2.08; p < 0.001 and HR 0.71; 95%CI 0.58-0.87; p < 0.001, respectively). NLR, PLR, and LMR are independent clinical predictors for overall survival in patients with rectal cancer treated with curative surgery. NLR and LMR are also good predictors for disease free survival. These biomarkers, which are readily available, appear optimal prognostic indexes and may help clinicians predict the prognosis of rectal cancer and develop individualized treatment strategies.

Novel Nomograms Based on Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio Predict Prognosis of Hepatocellular Carcinoma Patients After Hepatectomy.

The prediction of prognosis of hepatocellular carcinoma (HCC) is of great significance in improving disease outcome and optimizing clinical management, while reliable prognostic indicators are lacking. This study was conducted to develop readily-to-use nomograms for prognosis prediction of HCC after hepatectomy. Data of eligible patients were collected and analyzed retrospectively. Independent prognostic factors were identified by Cox regression, and nomograms for the prediction of disease-free survival (DFS) and overall survival (OS) were developed. The performance of the nomograms was evaluated by receiver operating characteristics (ROC) curves, C-indexes and calibration curves and was verified by the validation cohort. The predictive value of the nomograms was also compared with the 8th edition of American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) and the Barcelona Clinic Liver Cancer (BCLC) staging systems. In total, 599 patients were enrolled in the analysis: 420 in the training cohort and 179 in the validation cohort. The optimal cut-off value of Gamma-Glutamyl Transpeptidase-to-Lymphocyte Ratio (GLR) was 19.5. GLR contributed significantly to the nomograms with good predictive power. In ROC analyses, the areas under curve (AUCs) of the nomograms for 1-, 3- and 5-year DFS and OS prediction were 0.758, 0.756, 0.734 and 0.810, 0.799, 0.758, respectively. The C-indexes of the DFS nomogram were 0.697 (95% CI 0.665-0.729) in the training cohort and 0.710 (95% CI 0.664-0.756) in the validation cohort. For OS prediction, the C-indexes were 0.741 (95% CI 0.704-0.778) and 0.758 (95% CI 0.705-0.811) in the training and validation cohorts, respectively. The calibration curves demonstrated satisfactory agreement between nomogram predictions and actual observations. The nomograms demonstrated superior predictive performance to the TNM and the BCLC staging systems. Our novel nomograms showed adequate performance in the prediction of HCC prognosis after hepatectomy, which may facilitate the risk stratification and individualized management of HCC patients.

Nomograms for Predicting Disease-Free Survival Based on Core Needle Biopsy and Surgical Specimens in Female Breast Cancer Patients with Non-Pathological Complete Response to Neoadjuvant Chemotherapy

While a pathologic complete response (pCR) is regarded as a surrogate endpoint for pos-itive outcomes in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC), fore-casting the prognosis of non-pCR patients is still an open issue. This study aimed to create and evaluate nomogram models for estimating the likelihood of disease-free survival (DFS) for non-pCR patients. A retrospective analysis of 607 non-pCR BC patients was conducted (2012-2018). After converting continuous variables to categorical variables, variables entering the model were progressively identified by univariate and multivariate Cox regression analyses, and then pre-NAC and post-NAC nomogram models were developed. Regarding their discrimination, ac-curacy, and clinical value, the performance of the models was evaluated by internal and external validation. Two risk assessments were performed for each patient based on two models; patients were separated into different risk groups based on the calculated cut-off values for each model, including low-risk (assessed by the pre-NAC model) to low-risk (assessed by the post-NAC model), high-risk to low-risk, low-risk to high-risk, and high-risk to high-risk groups. The DFS of different groups was assessed using the Kaplan-Meier method. Both pre-NAC and post-NAC nomogram models were built with clinical nodal (cN) status and estrogen receptor (ER), Ki67, and p53 status (all p < 0.05), showing good discrimination and calibration in both internal and external validation. We also assessed the performance of the two models in four subtypes, with the tri-ple-negative subtype showing the best prediction. Patients in the high-risk to high-risk subgroup have significantly poorer survival rates (p < 0.0001). Two robust and effective nomo-grams were developed to personalize the prediction of DFS in non-pCR BC patients treated with NAC.

The survival outcomes of neoadjuvant sintilimab combined with chemotherapy in patients with locally advanced esophageal squamous cell carcinoma.

Neoadjuvant programmed death receptor-1 (PD-1) inhibitor combined with chemotherapy has been reported to improve the pathological response of locally advanced esophageal squamous cell carcinoma (ESCC), but the systematic report on survival follow-up is quite few. This study we will report the survival follow-up outcomes after a median follow-up of 21.1 months. This was a real-world retrospective study. Locally advanced ESCC patients treated with neoadjuvant sintilimab combined with albumin-bound paclitaxel and nedaplatin followed by surgery and completed at least 1-year follow-up were reviewed. The primary outcome was disease-free survival (DFS) at 24 months. The secondary outcome was overall survival (OS) at 24 months. Ninety eligible patients were included in the analysis between July 2019 and October 2021. The median number of neoadjuvant cycles was 3 (range 2-4). All patients achieved R0 resection. With a median follow-up of 21.1 months (range 14.0-39.0), the median DFS and median OS had not reached, 2-year DFS rate was 78.3% (95%CI 68.8%-89.1%) and 2-years OS rate was 88.0% (95%CI 80.6%-96.0%). Postoperative pathological stage, pCR, MPR, tumor down-staging were significantly correlated with favorable survival outcome. Univariable and multivariable Cox regression analysis identified cycle number of neoadjuvant treatment as independent predictor of DFS. Our results preliminarily show a survival benefit of neoadjuvant sintilimab combined with chemotherapy in locally advanced ESCC.

Novel biomarkers predict prognosis and drug-induced neuroendocrine differentiation in patients with prostate cancer.

A huge focus is being placed on the development of novel signatures in the form of new combinatorial regimens to distinguish the neuroendocrine (NE) characteristics from castration resistant prostate cancer (CRPC) timely and accurately, as well as predict the disease-free survival (DFS) and progression-free survival (PFS) of prostate cancer (PCa) patients. Single cell data of 4 normal samples, 3 CRPC samples and 3 CRPC-NE samples were obtained from GEO database, and CellChatDB was used for potential intercellular communication, Secondly, using the "limma" package (v3.52.0), we obtained the differential expressed genes between CRPC and CRPC-NE both in single-cell RNA seq and bulk RNA seq samples, and discovered 12 differential genes characterized by CRPC-NE. Then, on the one hand, the diagnosis model of CRPC-NE is developed by random forest algorithm and artificial neural network (ANN) through Cbioportal database; On the other hand, using the data in Cbioportal and GEO database, the DFS and PFS prognostic model of PCa was established and verified through univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression and multivariate Cox regression in R software. Finally, somatic mutation and immune infiltration were also discussed. Our research shows that there exists specific intercellular communication in classified clusters. Secondly, a CRPC-NE diagnostic model of six genes (HMGN2, MLLT11, SOX4, PCSK1N, RGS16 and PTMA) has been established and verified, the area under the ROC curve (AUC) is as high as 0.952 (95% CI: 0.882-0.994). The mutation landscape shows that these six genes are rarely mutated in the CRPC and NEPC samples. In addition, NE-DFS signature (STMN1 and PCSK1N) and NE-PFS signature (STMN1, UBE2S and HMGN2) are good predictors of DFS and PFS in PCa patients and better than other clinical features. Lastly, the infiltration levels of plasma cells, T cells CD4 naive, Eosinophils and Monocytes were significantly different between the CRPC and NEPC groups. This study revealed the heterogeneity between CRPC and CRPC-NE from different perspectives, and developed a reliable diagnostic model of CRPC-NE and robust prognostic models for PCa.

Prognostic factors of adult granulosa cell tumors of the ovary: a Turkish retrospective multicenter study.

To define the clinical, histopathological features and the prognostic factors affecting survival in patients with adult granulosa cell tumors of the ovary (AGCT). A 322 patients whose final pathologic outcome was AGCT treated at nine tertiary oncology centers between 1988 and 2021 participated in the study. The mean age of the patients was 51.3±11.8 years and ranged from 21 to 82 years. According to the International Federation of Gynecology and Obstetrics 2014, 250 (77.6%) patients were stage I, 24 (7.5%) patients were stage II, 20 (6.2%) patients were stage III, and 3 (7.8%) were stage IV. Lymphadenectomy was added to the surgical procedure in 210 (65.2%) patients. Lymph node involvement was noted in seven (3.3%) patients. Peritoneal cytology was positive in 19 (5.9%) patients, and 13 (4%) had metastases in the omentum. Of 285 patients who underwent hysterectomy, 19 (6.7%) had complex hyperplasia with atypia/endometrial intraepithelial neoplasia, and 8 (2.8%) had grade 1 endometrioid endometrial carcinoma. It was found that 93 (28.9%) patients in the study group received adjuvant treatment. Bleomycin, etoposide, cisplatin was the most commonly used chemotherapy protocol. The median follow-up time of the study group was 41 months (range, 1-276 months). It was noted that 34 (10.6%) patients relapsed during this period, and 9 (2.8%) patients died because of the disease. The entire cohort had a 5-year disease-free survival (DFS) of 86% and a 5-year disease-specific survival of 98%. Recurrences were observed only in the pelvis in 13 patients and the extra-abdominal region in 7 patients. The recurrence rate increased 6.168-fold in patients with positive peritoneal cytology (95% confidence interval [CI]=1.914-19.878; p=0.002), 3.755-fold in stage II-IV (95% CI=1.275-11.063; p=0.016), and 2.517-fold in postmenopausal women (95% CI=1.017-6.233; p=0.046) increased. In this study, lymph node involvement was detected in 3.3% of patients with AGCT. Therefore, it was concluded that lymphadenectomy can be avoided in primary surgical treatment. Positive peritoneal cytology, stage, and menopausal status were independent prognostic predictors of DFS.

Synchronous endometrial and ovarian cancer and its recurrent risk factors: Case series

BackgroundSynchronous endometrial and ovarian cancer (SEOC) is a relatively rare entity with indistinct clinical manifestation but have a better prognosis compared to metastatic malignancy of each organ. The aim of the study is to determine the prognosis and factors associated with recurrence of SEOC. MethodsThis case-series study was performed on 37 histologically confirmed SEOC, diagnosed and treated in our tertiary hospital from March 2009 to September 2021. Disease-free survival (DFS) and overall survival (OS) rates following indicated procedure were calculated using the Kaplan-Meier method. Univariate and multivariate Cox regression analysis were used to determine risk factors of recurrence. ResultsThe mean age of participants was 49.38 (age range: 26–78). The most common complaints and symptoms were abdominal pain (40.5%), followed by abnormal uterine bleeding (29.7%). Most common histological presentation was endometroid type for both ovarian (46%) and endometrial (97.3%) cancers. Over the mean follow-up period of 85.54 months, 11 patients developed recurrence without mortality. Non-endometrioid histology of ovarian cancer, higher grade and stage of ovarian cancer, and omentum invasion were significantly associated with worse DFS in unvariate analysis. Lymphovascular invasion was the sole predictor of DFS in multivariate analysis. ConclusionWhile this study was not able to investigate the risk factors of overall survival associated with SEOC, the results of this study provides an overview of clinicopathological presentation of the disease and emphasizes the importance of lymphovascular invasion in determining prognosis and DFS in SEOC.