scholarly journals Validation of onco-assist survival prediction tool in stage I, II and IIIcolon cancer among Asian patients

2021 ◽  
Vol 3 (4) ◽  
pp. 107-111
Author(s):  
Fayaz Hussain Mangi ◽  
Jawaid Naeem Qureshi
Keyword(s):  
Colon Cancer ◽  
Survival Rate ◽  
Lymph Nodes ◽  
Cancer Survival ◽  
Asian Population ◽  
Stage I ◽  
Prediction Algorithm ◽  
Survival Prediction ◽  
Institute Of Medicine ◽  
Poorly Differentiated

Clinical calculators and predictors are now commonly used in clinical practice to predict most accurate clinical outcome and provide guidance for appropriate therapy. One of the most used calculator is Onco-assist. This study was conducted to compare onco-assist prediction of the patients diagnosed with colon cancer Stage I, II and III. Data was retrospectively collected from 88 patients of colon cancer diagnosed over the period of 11 years (2008 to 2018) and registered at Nuclear Institute of medicine and radiotherapy (NIMRA), Hospital, Jamshoro Sindh. These patients received primary surgical therapy without any neo-adjuvant systemic chemotherapy. Survival assessed on onco-assist prediction algorithm using the defined parameters and compared with the actual survival according to the grade of the tumour. The clinical calculator onco-assist incorporated seven variables: gender, age number of lymph nodes examined, number of tumor-involved lymph nodes, T = (1-4), grade (low / high), adjuvant chemo received (yes / no) if yes then only 5FU or 5FU plus Oxaliplatin based. Onco-assist predicted five-year survival rate in well differentiated tumours with and without chemotherapy as 84% and 80% respectively, in moderately differentiated tumour with and without chemotherapy as 78% and 76% respectively. For poorly differentiated tumours the predicted survival rate with and without chemotherapy was 73%. While actual achieved survival was 35%, 52% and 17% for well, moderately and poorly differentiated cancers. This clinical calculator onco-assist includes limited parameters and limited adjuvant therapy options thus the prediction of cancer survival following surgery in stage I –III colon cancer does not appear to accurately predict outcome in Asian population.

scholarly journals Impact of the Number of Dissected Lymph Nodes on Survival for Gastric Cancer after Distal Subtotal Gastrectomy

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Chang-Ming Huang ◽  
Jian-Xian Lin ◽  
Chao-Hui Zheng ◽  
Ping Li ◽  
Jian-Wei Xie ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Survival Rate ◽  
Lymph Nodes ◽  
Distal Gastrectomy ◽  
Stage I ◽  
Stage Ii ◽  
Stage Iii ◽  
Prognostic Impact ◽  
Term Survival

Objectives. To investigate the prognostic impact of the number of dissected lymph nodes (LNs) in gastric cancer after curative distal gastrectomy.Methods. The survival of 634 patients who underwent curative distal gastrectomy from 1995 to 2004 was retrieved. Long-term surgical outcomes and associations between the number of dissected LNs and the 5-year survival rate were investigated.Results. The number of dissected LNs was one of the most important prognostic indicators. Among patients with comparable T category, the larger the number of dissected LNs was, the better the survival would be (). The linear regression showed that a significant survival improvement based on increasing retrieved LNs for stage II, III and IV (). A cut-point analysis yields the greatest variance of survival rate difference at the levels of 15 LNs (stage I), 25 LNs (stage II) and 30 LNs (stage III).Conclusion. The number of dissected LNs is an independent prognostic factor for gastric cancer. To improve the long-term survival of patients with gastric cancer, removing at least 15 LNs for stage I, 25 LNs for stage II, and 30 LNs for stage III patients during curative distal gastrectomy is recommended.

Effect of tumor progression on colon cancer stem cell plasticity.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 688-688
Author(s):  
Vi Kien Chiu ◽  
Rama Gallupalli ◽  
Diaa Osman ◽  
Zhaoshi Zeng ◽  
Jinru Shia ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Stem Cell ◽  
Stage Iv ◽  
Human Colon ◽  
Stage I ◽  
Normal Colon ◽  
Colon Adenoma ◽  
Colon Cancer Stem Cell ◽  
Tumor Plasticity ◽  
Poorly Differentiated

688 Background: Stage I colon cancer initiation is optimized through the activation of the embryonic stem cell (SC)-like program in colon adenoma cells (Le Rolle AF, et al., 2016). This malignant transformation requires cellular dedifferentiation since the embryonic SC-like program does not exist a priori in colon cells. High initial tumor plasticity provides a competitive advantage as the tumor has more intrinsic phenotypic flexibility to survive environmental challenges. Inhibition of the embryonic SC-like program represents a novel therapeutic strategy. Herein, we examine the evolution this high tumor plasticity in stage I-IV colon cancer. Methods: Human colon cancer tissues were collected prospectively under an MSKCC IRB protocol (Jan 1990-Dec 2000). RNA in situ hybridization of LGR5, a colon SC marker, was carried out on human colon tumors before and after therapeutic interventions. We performed Gene Set Enrichment Analysis (GSEA 2.0 Broad Institute software) using Affymetrix U133A expression profiles from normal colon mucosa (n = 33) and colon cancer epithelia from stage I (n = 17), II (n = 35), III (n= 39) and IV (n= 46) tumors. Statistical analyses were conducted with GraphPad Prism 5 and Microsoft Excel. Results: Putative colon SC markers and differentiation markers are increased and decreased, respectively, in stage I-IV colon cancer in comparison to normal colon. Although colon adenoma originates from LGR5+ colon SC, LGR5+ overexpression per se correlates with good prognosis stage IV colon cancer and is not a colon cancer stem cell biomarker. Maximal embryonic SC-like program enrichment occurs in stage I colon cancer. GSEA comparisons of moderately differentiated stages II-IV versus stage I colon cancer reveal progressive tumor differentiation from the stage I embryonic SC-like program toward the intestinal SC program at more advanced tumor stages. Notably, poorly differentiated stage IV colon cancer retains an embryonic SC-like program. Conclusions: We conclude that except for poorly differentiated tumors, colon cancer progression from stage I to IV involves a heterogeneous tumor differentiation process from an embryonic SC-like program towards the intestinal SC or more differentiated intestinal cell programs.

Retrospective Analysis of Selective Lymphadenectomy in Apparent Early-Stage Endometrial Cancer

2005 ◽  
Vol 23 (16) ◽  
pp. 3668-3675 ◽  
Author(s):  
Janiel M. Cragun ◽  
Laura J. Havrilesky ◽  
Brian Calingaert ◽  
Ingrid Synan ◽  
Angeles Alvarez Secord ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Lymph Nodes ◽  
Proportional Hazards Model ◽  
Early Stage ◽  
Clinical Stage ◽  
Cox Proportional Hazards Model ◽  
Stage I ◽  
Selective Lymphadenectomy ◽  
Poorly Differentiated ◽  
Early Stage Endometrial Cancer

Purpose Selective lymphadenectomy is widely accepted in the management of endometrial cancer. Purported benefits are individualization of adjuvant therapy based on extent of disease and resection of occult metastases. Our goal was to assess effects of the extent of selective lymphadenectomy on outcomes in women with apparent stage I endometrial cancer at laparotomy. Patients and Methods Patients with endometrial cancer who received primary surgical treatment between 1973 and 2002 were identified through an institutional tumor registry. Inclusion criteria were clinical stage I/IIA disease and procedure including hysterectomy and selective lymphadenectomy (pelvic or pelvic + aortic). Exclusion criteria included presurgical radiation, grossly positive lymph nodes, or extrauterine metastases at laparotomy. Recurrence and survival were analyzed using Kaplan-Meier analysis and Cox proportional hazards model. Results Among 509 patients, the median number of lymph nodes removed was 15 (median pelvic, 11; median aortic, three). Pelvic and aortic node metastases were found in 24 (5%) of 509 patients and 11 (3%) of 373 patients, respectively. Patients with poorly differentiated cancers having more than 11 pelvic nodes removed had improved overall survival (hazard ratio [HR], 0.25; P < .0001) and progression-free survival (HR, 0.26; P < .0001) compared with patients having poorly differentiated cancers with 11 or fewer nodes removed. Number of nodes removed was not predictive of survival among patients with cancers of grade 1 to 2. Performance of aortic selective lymphadenectomy was not associated with survival. Three (27%) of 11 patients with microscopic aortic nodal metastasis are alive without recurrence. Conclusion These data add to the literature documenting the possible therapeutic benefit of selective lymphadenectomy in management of patients with apparent early-stage endometrial cancer.

scholarly journals PROGNOSTIC SIGNIFICANCE OF REARRANGEMENTS OF EML4-ALK IN PATIENTS WITH STAGE TI-II ADENOCARCINOMA IN THE RELATIONSHIP WITH SOME CLINICAL AND MORPHOLOGICAL PARAMETERS

2017 ◽  
Vol 22 (4) ◽  
pp. 194-197
Author(s):  
Ashot M. Avdalyan ◽  
A. U Panasyan ◽  
A. A Ivanov ◽  
O. V Samuilenkova ◽  
S. Y Bakharev ◽  
...  
Keyword(s):  
Survival Rate ◽  
Lymph Nodes ◽  
Prognostic Significance ◽  
Stage I ◽  
Immunohistochemical Method ◽  
Her2 Gene ◽  
Gene Status ◽  
The Relationship

The purpose of the study: determination of ALK gene status (mutation) in patients with stage TI-II adenocarcinoma in the relationship with survival, stage, size, metastases in bronchopulmonary lymph nodes and the amplification of Her2/Neu. Materials. 98 stage I-II adenocarcinoma patients. Cases with a mutation in ALK account for 20 (4.8% without randomization). There was used the immunohistochemical method and in situ hybridization. Results. The survival rate of adenocarcinoma patients with metastases in the lymph nodes was lower than in cases without metastases: 8.3 ± 7.8% and 40.9 ± 13% respectively. None of patients with a mutation ALK lived up to 9 years in contrast to the cases without mutations (37.4 ± 12.6%). In the presence of amplification of the Her2 gene survival rate in adenocarcinoma patients was lower if compared to cases without amplification (p = 0.02). Correlation between ALK mutation and amplification of Her2 with increased N is not revealed. Thus, an independent criterion of the prognosis for cases with of stage I-II lung adenocarcinoma is the N index (χ2 = 9.6, p = 0.001). The rate of mutation of ALK was lower, but had the second largest impact on the prognosis (χ2 = 7.7, p = 0.005).

scholarly journals Predicting breast cancer 5-year survival using machine learning: A systematic review

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250370
Author(s):  
Jiaxin Li ◽  
Zijun Zhou ◽  
Jianyu Dong ◽  
Ying Fu ◽  
Yuan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Systematic Review ◽  
Survival Rate ◽  
Cancer Survival ◽  
Model Performance ◽  
Support Vector ◽  
Survival Prediction ◽  
Breast Cancer Patients ◽  
Modeling Process

Background Accurately predicting the survival rate of breast cancer patients is a major issue for cancer researchers. Machine learning (ML) has attracted much attention with the hope that it could provide accurate results, but its modeling methods and prediction performance remain controversial. The aim of this systematic review is to identify and critically appraise current studies regarding the application of ML in predicting the 5-year survival rate of breast cancer. Methods In accordance with the PRISMA guidelines, two researchers independently searched the PubMed (including MEDLINE), Embase, and Web of Science Core databases from inception to November 30, 2020. The search terms included breast neoplasms, survival, machine learning, and specific algorithm names. The included studies related to the use of ML to build a breast cancer survival prediction model and model performance that can be measured with the value of said verification results. The excluded studies in which the modeling process were not explained clearly and had incomplete information. The extracted information included literature information, database information, data preparation and modeling process information, model construction and performance evaluation information, and candidate predictor information. Results Thirty-one studies that met the inclusion criteria were included, most of which were published after 2013. The most frequently used ML methods were decision trees (19 studies, 61.3%), artificial neural networks (18 studies, 58.1%), support vector machines (16 studies, 51.6%), and ensemble learning (10 studies, 32.3%). The median sample size was 37256 (range 200 to 659820) patients, and the median predictor was 16 (range 3 to 625). The accuracy of 29 studies ranged from 0.510 to 0.971. The sensitivity of 25 studies ranged from 0.037 to 1. The specificity of 24 studies ranged from 0.008 to 0.993. The AUC of 20 studies ranged from 0.500 to 0.972. The precision of 6 studies ranged from 0.549 to 1. All of the models were internally validated, and only one was externally validated. Conclusions Overall, compared with traditional statistical methods, the performance of ML models does not necessarily show any improvement, and this area of research still faces limitations related to a lack of data preprocessing steps, the excessive differences of sample feature selection, and issues related to validation. Further optimization of the performance of the proposed model is also needed in the future, which requires more standardization and subsequent validation.

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