scholarly journals Nomogram to predict overall survival for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Pseudomyxoma Peritonei ◽  
Roc Analysis ◽  
Prediction Models ◽  
Radical Surgery ◽  
Individual Risk ◽  
Good Discrimination ◽  
Internal Validation ◽  
Discrimination Ability ◽  
First Time

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to define independent prediction indicators and establish a nomogram for PMP patients.Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for defining independent prediction indicators. Finally, the nomogram prediction models will be established and for internal validation.Results Multivariate analysis showed Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery were independently associated with OS in PMP patients. A nomogram was plotted based on the independent predictive factors and undergone internal validation, ROC analysis was performed to calculate discrimination ability of the nomogram, the C-index was 0.880 (95%CI: 0.806- 0.933) and calibration plots showed good performance. Conclusions Six independent prognostic factor for predicting survival in PMP patients were difined, the nomogram has a good discrimination ability for individual risk predition, more researches are needed to verify and improve the prediction model.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Roc Analysis ◽  
Prediction Models ◽  
Radical Surgery ◽  
Univariate Analysis ◽  
Barthel Index Score ◽  
Discrimination Ability ◽  
First Time ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators for PMP and establish prediction model for OS rates in PMP.Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the prediction models for OS in PMP will be established.Results Univariate analysis showed that Barthel Index Score, albumin, D-dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, sex, D-dimer, CA125, CA19-9, and degree of radical surgery were independently associated with OS rate in PMP. ROC analysis was performed to calculate discrimination ability of prediction model and the area under curves (AUC) was 0.902 (95%CI: 0.823-0.954). Finally, nomogram was plotted by the independent predictive factors for PMP.Conclusions Several factors (sex, degree of radical surgery, D-dimer, preoperative CA125 and CA19-9) have independent prognostic value for survival in PMP, the tumor based prediction model has better prediction value, more researches are need to verify and improve the prediction model.

scholarly journals Tumor marker based survival analysis for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Prediction Model ◽  
Pseudomyxoma Peritonei ◽  
Prediction Models ◽  
Radical Surgery ◽  
Cox Model ◽  
Univariate Analysis ◽  
Rank Test ◽  
Internal Validation ◽  
Discrimination Ability ◽  
D Dimer

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to screen independent prediction indicators and establish a nomogram for PMP. Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for screening independent prediction indicators. Finally, the nomogram prediction models will be established. Results Univariate analysis showed that Barthel Index Score, Albumin, D-Dimer, CEA, CA125, CA19-9, CA724, CA242, PCI, degree of radical surgery, histopathological grade were significant predictors for OS in PMP. At multivariate analysis, Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery were independently associated with OS rate in PMP. A nomogram was plotted based on the independent predictive factors for PMP and undergone internal validation, ROC analysis was performed to calculate discrimination ability of prediction model, the area under curves (AUC) was 0.880 (95% CI : 0.806- 0.933). Conclusions Several factors (Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery) have independent prognostic value for survival in PMP, the tumor based prediction model has a better prediction value, more researches are need to verify and improve the prediction model.

scholarly journals Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihao Lv ◽  
Yuqi Liang ◽  
Huaxi Liu ◽  
Delong Mo
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Prediction Models ◽  
Radical Surgery ◽  
Survival Rates ◽  
Stage Ii ◽  
Survival Prediction ◽  
Stage Ii Colon Cancer ◽  
Overall Survival Rates

Abstract Background It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. Methods Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. Results A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. Conclusions Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

scholarly journals Identification and Characterization of Circular RNA as a Novel Regulator and Biomarker in Preterm Birth

2020 ◽  
Vol 8 ◽  
Author(s):  
Yuxin Ran ◽  
Nanlin Yin ◽  
Dongni Huang ◽  
Yangyu Zhao ◽  
Jing Yang ◽  
...  
Keyword(s):  
Preterm Birth ◽  
Roc Analysis ◽  
Underlying Mechanism ◽  
Circular Rna ◽  
Diagnosis And Treatment ◽  
Rna Seq ◽  
Discrimination Ability ◽  
First Time ◽  
Identification And Characterization

Preterm birth (PTB), as the leading cause of neonatal death, is a severe threat to maternal–fetal health. The diagnosis and treatment of PTB are difficult as its underlying mechanism still unknown. Circular RNA (circRNA) is an emerging molecule that plays an essential role in the pathological processes of various diseases. However, it is still unclear whether circRNAs are abnormal or involves in the PTB pathology. In this study, we analyzed RNA-seq data of peripheral blood from preterm and term pregnant women and verified with microarray data. There were 211 circRNA expression disorders in PTB, of which 68 increased and 143 decreased. Bioinformatics analysis revealed that the top 20 circRNAs competitively bind 68 miRNAs, thereby regulating 622 mRNAs mainly related to immunity, inflammation, and nerve activity, which may ultimately contribute to the occurrence of PTB. Moreover, 6 regulatory pairs, including hsa-MORC3_0001–hsa-miR-1248–CHRM2 were the core parts of this mechanism network, which might be therapeutic targets for PTB. Besides, ROC analysis indicated that hsa-ANKFY1_0025, hsa-FAM13B_0019, and hsa-NUSAP1_0010 (AUC = 0.7138, 0.9589, 1.000) have an excellent discrimination ability for PTB. Taken together, we explored for the first time the circRNA expression profile of PTB, and preliminarily analyzed its regulatory mechanism and predictive value for PTB, thus bringing new light to the diagnosis and treatment of PTB.

scholarly journals A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

2021 ◽  
Author(s):  
Alice Sabrina Tonello ◽  
Giulia Capelli ◽  
Quoc Riccardo Bao ◽  
Alberto Marchet ◽  
Fabio Farinati ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Disease Free Survival ◽  
Tumor Location ◽  
Good Discrimination ◽  
Curative Intent ◽  
Cox Models ◽  
Internal Validation ◽  
Discrimination Ability ◽  
Node Ratio ◽  
N Stage

AbstractAn individual prediction of DFS and OS may be useful after surgery for gastric cancer to inform patients and to guide the clinical management. Patients who underwent curative-intent resection for gastric cancer between January 2010 and May 2020 at a single Italian institution were identified. Variables associated with OS and DFS were recorded and analysed according to univariable and multivariable Cox models. Nomograms predicting OS and DFS were built according to variables resulting from multivariable Cox models. Discrimination ability was calculated using the Harrell’s Concordance Index. Overall, 168 patients underwent curative-intent resection. Nomograms to predict OS were developed including age, tumor size, tumor location, T stage, N stage, M stage and post-operative complications, while nomogram to predict DFS includes Lauren classification, and lymph node ratio (LNR). On internal validation, both nomograms demonstrated a good discrimination with a Harrell’s C-index of 0.77 for OS and 0.71 for DFS. The proposed nomogram to predict DFS and OS after curative-intent surgery for gastric cancer showed a good discrimination on internal validation, and may be useful to guide clinician decision-making, as well help identify patients with high-risk of recurrence or with a poor estimated survival.

scholarly journals Nomograms Predict Overall Survival and Cancer-Specific Survival in Patients with Fibrosarcoma: A SEER-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Guang-Heng Xiang ◽  
Juan-Juan Zhu ◽  
Chen-Rong Ke ◽  
Yi-Min Weng ◽  
Ming-Qiao Fang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Discrimination Performance ◽  
Tumor Stage ◽  
Good Discrimination ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Clinical Benefits

Purpose. Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma. Methods. A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3-year and 5‐year overall survival and cancer‐specific survival of patients with fibrosarcoma. Results. In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery, and tumor size were identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery, and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3-year and 5-year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the C-indices were 0.784 and 0.801. Conclusion. We developed the nomograms that estimated 3-year and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration but also provide patients with better clinical benefits.

scholarly journals Nomograms Predict Overall Survival And Cancer-Specific Survival In Patients With Fibrosarcoma: A SEER-Based Study

2020 ◽  
Author(s):  
Guangheng Xiang ◽  
Juan-Juan Zhu ◽  
Chen-Rong Ke ◽  
Yi-Min Weng ◽  
Ming-Qiao Fang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Discrimination Performance ◽  
Tumor Stage ◽  
Good Discrimination ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Clinical Benefits

Abstract Background Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma. Methods A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3‐ and 5‐year overall survival and cancer‐specific survival of patients with fibrosarcoma. Results In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery and tumor size identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3- and 5- year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the C-indices were 0.784 and 0.801. Conclusion We developed and validated the nomograms that estimated 3- and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration, but also provide patients with better clinical benefits.

scholarly journals Development and internal validation of a prediction model of prostate cancer on initial transperineal template-guided prostate biopsy

BMC Urology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuliang Chen ◽  
Zhien Zhou ◽  
Yi Zhou ◽  
Xingcheng Wu ◽  
Yu Xiao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Prediction Model ◽  
Prostate Biopsy ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Good Discrimination ◽  
Internal Validation ◽  
Discrimination Ability ◽  
Guided Biopsy

Abstract Background Due to the invasiveness of prostate biopsy, a prediction model of the individual risk of a positive biopsy result could be helpful to guide clinical decision-making. Most existing models are based on transrectal ultrasonography (TRUS)-guided biopsy. On the other hand, transperineal template-guided prostate biopsy (TTPB) has been reported to be more accurate in evaluating prostate cancer. The objective of this study is to develop a prediction model of the detection of high-grade prostate cancer (HGPC) on initial TTPB. Result A total of 1352 out of 3794 (35.6%) patients were diagnosed with prostate cancer, 848 of whom had tumour with Grade Group 2–5. Age, PSA, PV, DRE and f/t PSA are independent predictors of HGPC with p < 0.001. The model showed good discrimination ability (c-index 0.886) and calibration during internal validation and good clinical performance was observed through decision curve analysis. The external validation of CPCC-RC, an existing model, demonstrated that models based on TRUS-guided biopsy may underestimate the risk of HGPC in patients who underwent TTPB. Conclusion We established a prediction model which showed good discrimination ability and calibration in predicting the detection of HGPC by initial TTPB. This model can be used to aid clinical decision making for Chinese patients and other Asian populations with similar genomic backgrounds, after external validations are conducted to further confirm its clinical applicability.

4 Pattern Recognition for Healing Burns to Compute Evidence: Space Syntax and Machine Learning Analysis of Burns Center Karachi

2013 ◽  
Vol 1 (1) ◽  
pp. 13
Author(s):  
Javaria Manzoor Shaikh ◽  
JaeSeung Park
Keyword(s):  
Pattern Recognition ◽  
Prediction Models ◽  
Uv Light ◽  
Healing Process ◽  
Space Syntax ◽  
Depth Map ◽  
Routine Tasks ◽  
Hyper Plane ◽  
First Time ◽  
Learning Analysis

Usually elongated hospitalization is experienced byBurn patients, and the precise forecast of the placement of patientaccording to the healing acceleration has significant consequenceon healthcare supply administration. Substantial amount ofevidence suggest that sun light is essential to burns healing andcould be exceptionally beneficial for burned patients andworkforce in healthcare building. Satisfactory UV sunlight isfundamental for a calculated amount of burn to heal; this delicaterather complex matrix is achieved by applying patternclassification for the first time on the space syntax map of the floorplan and Browder chart of the burned patient. On the basis of thedata determined from this specific healthcare learning technique,nurse can decide the location of the patient on the floor plan, hencepatient safety first is the priority in the routine tasks by staff inhealthcare settings. Whereas insufficient UV light and vitamin Dcan retard healing process, hence this experiment focuses onmachine learning design in which pattern recognition andtechnology supports patient safety as our primary goal. In thisexperiment we lowered the adverse events from 2012- 2013, andnearly missed errors and prevented medical deaths up to 50%lower, as compared to the data of 2005- 2012 before this techniquewas incorporated.In this research paper, three distinctive phases of clinicalsituations are considered—primarily: admission, secondly: acute,and tertiary: post-treatment according to the burn pattern andhealing rate—and be validated by capable AI- origin forecastingtechniques to hypothesis placement prediction models for eachclinical stage with varying percentage of burn i.e. superficialwound, partial thickness or full thickness deep burn. Conclusivelywe proved that the depth of burn is directly proportionate to thedepth of patient’s placement in terms of window distance. Ourfindings support the hypothesis that the windowed wall is mosthealing wall, here fundamental suggestion is support vectormachines: which is most advantageous hyper plane for linearlydivisible patterns for the burns depth as well as the depth map isused.

Neoadjuvant chemotherapy followed by radical surgery in locally advanced vulvar carcinoma: a single-institution experience

2021 ◽  
pp. 030089162110276
Author(s):  
Adorni Marco ◽  
Bazzurini Luca ◽  
Lissoni Andrea Alberto ◽  
Vecchione Francesca ◽  
Negri Serena ◽  
...  
Keyword(s):  
Overall Survival ◽  
Neoadjuvant Chemotherapy ◽  
Partial Response ◽  
Vulvar Cancer ◽  
Elderly Women ◽  
Radical Surgery ◽  
Locally Advanced ◽  
Complete Response ◽  
Tumor Burden ◽  
Clinical Response Rate

Background: Squamous cell carcinoma of the vulva is a rare malignancy that affects elderly women. About one-third of vulvar cancers are diagnosed in an advanced stage, requiring extensive surgery. Neoadjuvant chemotherapy (NACT) has been introduced to reduce local tumor burden. In this retrospective study, we analyze the efficacy and toxicity of NACT followed by radical surgery. Methods: Patients with locally advanced vulvar cancer (LAVC) treated at our institution with neoadjuvant platinum and paclitaxel-based chemotherapy ± ifosfamide followed by surgery at our institution were retrospectively identified. Results: Fourteen patients (93%) completed NACT with tolerable toxicities (G3–G4 toxicity: 30%). Thirteen patients (87%) underwent surgery. The overall clinical response rate on vulvar disease was 66% (20% complete response, 46% partial response), confirmed by histopathologic analysis, while on inguinal lymph nodes it was 69% (23% complete response, 46% partial response). At the pathologic examination, all patients had negative surgical margins. Three out of 9 patients (33%) with lesions infiltrating the urethral meatus and 4 patients out of 7 (57%) with anal involvement did not require urethral amputation or colostomy, respectively, after NACT. No severe postoperative complications were described. Overall survival at 5 years was 60%, and median overall survival was 76 months. Conclusion: NACT followed by surgery in locally advanced vulvar cancer is well tolerated and allows surgical modulation.

Sign in / Sign up

Export Citation Format

Share Document