Jiayun Zhong, Yu Liu, Qian Fu, Dan Huang, Wenjun Gong, Jian Zou
Background: Regorafenib, a novel multikinase inhibitor, has been approved by the US Food and Drug Administration as a standard treatment choice for metastatic colorectal cancer (mCRC). Nonetheless, its substantial cost places a significant burden on social health resources and patients. However, the cost-effectiveness (CE) of regorafenib compared to other third-line therapies is still undetermined. Objective: This study aims to assess the CE of regorafenib compared to other third-line therapies for the treatment of mCRC. Methods: We conducted a comprehensive literature search in PubMed, Medline, Scopus, Embase, Cochrane Library, as well as nine other databases to identify relevant studies published up to October 2023, focusing on patients with mCRC and examining the cost-effectiveness of regorafenib. Following the screening and extraction of pertinent data, the study quality was assessed using the Quality of Health Economic Studies (QHES) checklist. Results: The literature search yielded 751 records, and after applying the inclusion criteria, 13 studies from 7 different countries were included. Of these, 7 studies evaluated the cost-effectiveness of regorafenib compared to trifluridine/tipiracil (TAS-102), 3 studies compared regorafenib with best supportive care (BSC), and 3 studies compared regorafenib with fruquintinib, serplulimab, and regorafenib dose optimization (ReDo).The quality of the included studies was high with an average QHES scores of 85.62. Regorafenib standard dose proves to be less cost-effective than alternative third-line therapies. Implementing a dose optimization strategy could potentially rectify this disparity and enhance the cost-effectiveness of regorafenib. Conclusion: The use of the standard dose of regorafenib is generally regarded as not cost-effective when compared to other third-line therapies for patients with mCRC. However, implementing a dose-escalation strategy may enhance regorafenib’s cost-effectiveness. Consequently, significant price reductions or optimizing the dose of regorafenib are required to achieve cost-effectiveness.
{"title":"Cost-Effectiveness Analysis of Regorafenib versus Other Third-Line Treatments for Metastatic Colorectal Cancer","authors":"Jiayun Zhong, Yu Liu, Qian Fu, Dan Huang, Wenjun Gong, Jian Zou","doi":"10.2147/cmar.s464831","DOIUrl":"https://doi.org/10.2147/cmar.s464831","url":null,"abstract":"<strong>Background:</strong> Regorafenib, a novel multikinase inhibitor, has been approved by the US Food and Drug Administration as a standard treatment choice for metastatic colorectal cancer (mCRC). Nonetheless, its substantial cost places a significant burden on social health resources and patients. However, the cost-effectiveness (CE) of regorafenib compared to other third-line therapies is still undetermined.<br/><strong>Objective:</strong> This study aims to assess the CE of regorafenib compared to other third-line therapies for the treatment of mCRC.<br/><strong>Methods:</strong> We conducted a comprehensive literature search in PubMed, Medline, Scopus, Embase, Cochrane Library, as well as nine other databases to identify relevant studies published up to October 2023, focusing on patients with mCRC and examining the cost-effectiveness of regorafenib. Following the screening and extraction of pertinent data, the study quality was assessed using the Quality of Health Economic Studies (QHES) checklist.<br/><strong>Results:</strong> The literature search yielded 751 records, and after applying the inclusion criteria, 13 studies from 7 different countries were included. Of these, 7 studies evaluated the cost-effectiveness of regorafenib compared to trifluridine/tipiracil (TAS-102), 3 studies compared regorafenib with best supportive care (BSC), and 3 studies compared regorafenib with fruquintinib, serplulimab, and regorafenib dose optimization (ReDo).The quality of the included studies was high with an average QHES scores of 85.62. Regorafenib standard dose proves to be less cost-effective than alternative third-line therapies. Implementing a dose optimization strategy could potentially rectify this disparity and enhance the cost-effectiveness of regorafenib.<br/><strong>Conclusion:</strong> The use of the standard dose of regorafenib is generally regarded as not cost-effective when compared to other third-line therapies for patients with mCRC. However, implementing a dose-escalation strategy may enhance regorafenib’s cost-effectiveness. Consequently, significant price reductions or optimizing the dose of regorafenib are required to achieve cost-effectiveness.<br/><br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"3 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<strong>Purpose:</strong> In situations where pathological acquisition is difficult, there is a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging images, and each doctor can only make judgments based on their own experience. This study aims to extract imaging features of chest CT, extract sensitive factors through logistic univariate and multivariate analysis, and model to distinguish between lung squamous cell carcinoma and lung adenocarcinoma.<br/><strong>Methods:</strong> We downloaded chest CT scans with clear diagnosis of adenocarcinoma and squamous cell carcinoma from The Cancer Imaging Archive (TCIA), extracted 19 imaging features by a radiologist and a thoracic surgeon, including location, spicule, lobulation, cavity, vacuolar sign, necrosis, pleural traction sign, vascular bundle sign, air bronchogram sign, calcification, enhancement degree, distance from pulmonary hilum, atelectasis, pulmonary hilum and bronchial lymph nodes, mediastinal lymph nodes, interlobular septal thickening, pulmonary metastasis, adjacent structures invasion, pleural effusion. Firstly, we apply the glm function of R language to perform logistic univariate analysis on all variables to select variables with P < 0.1. Then, perform logistic multivariate analysis on the selected variables to obtain a predictive model. Next, use the roc function in R language to calculate the AUC value and draw the ROC curve, use the val.prob function in R language to draw the Calibrat curve, and use the rmda package in R language to draw the DCA curve and clinical impact curve. At the same time, 45 patients diagnosed with lung squamous cell carcinoma and lung adenocarcinoma through surgery or biopsy in the Radiotherapy Department and Thoracic Surgery Department of our hospital from 2023 to 2024 were included in the validation group. The chest CT features were jointly determined and recorded by the two doctors mentioned above and included in the validation group. The included image feature data are complete and does not require preprocessing, so directly entering statistical calculations. Perform ROC curves, calibration curves, DCA, and clinical impact curves in the validation group to further validate the predictive model. If the predictive model performs well in the validation group, further draw a nomogram to demonstrate.<br/><strong>Results:</strong> This study extracted 19 imaging features from the chest CT scans of 75 patients downloaded from TCIA and finally selected 18 complete data for analysis. First, univariate analysis and multivariate analysis were performed, and a total of 5 variables were obtained: spicule, necrosis, air bronchogram Sign, atelectasis, pulmonary hilum and bronchial lymph nodes. After conducting modeling analysis with AUC = 0.887, a validation group was established using clinical cases from our hospital, Draw ROC curve with AUC = 0.865 in the validation group, evaluate the accuracy of the model through C
{"title":"Application of Chest CT Imaging Feature Model in Distinguishing Squamous Cell Carcinoma and Adenocarcinoma of the Lung","authors":"Chunmei Liu, Yuzheng He, Jianmin Luo","doi":"10.2147/cmar.s462951","DOIUrl":"https://doi.org/10.2147/cmar.s462951","url":null,"abstract":"<strong>Purpose:</strong> In situations where pathological acquisition is difficult, there is a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging images, and each doctor can only make judgments based on their own experience. This study aims to extract imaging features of chest CT, extract sensitive factors through logistic univariate and multivariate analysis, and model to distinguish between lung squamous cell carcinoma and lung adenocarcinoma.<br/><strong>Methods:</strong> We downloaded chest CT scans with clear diagnosis of adenocarcinoma and squamous cell carcinoma from The Cancer Imaging Archive (TCIA), extracted 19 imaging features by a radiologist and a thoracic surgeon, including location, spicule, lobulation, cavity, vacuolar sign, necrosis, pleural traction sign, vascular bundle sign, air bronchogram sign, calcification, enhancement degree, distance from pulmonary hilum, atelectasis, pulmonary hilum and bronchial lymph nodes, mediastinal lymph nodes, interlobular septal thickening, pulmonary metastasis, adjacent structures invasion, pleural effusion. Firstly, we apply the glm function of R language to perform logistic univariate analysis on all variables to select variables with P < 0.1. Then, perform logistic multivariate analysis on the selected variables to obtain a predictive model. Next, use the roc function in R language to calculate the AUC value and draw the ROC curve, use the val.prob function in R language to draw the Calibrat curve, and use the rmda package in R language to draw the DCA curve and clinical impact curve. At the same time, 45 patients diagnosed with lung squamous cell carcinoma and lung adenocarcinoma through surgery or biopsy in the Radiotherapy Department and Thoracic Surgery Department of our hospital from 2023 to 2024 were included in the validation group. The chest CT features were jointly determined and recorded by the two doctors mentioned above and included in the validation group. The included image feature data are complete and does not require preprocessing, so directly entering statistical calculations. Perform ROC curves, calibration curves, DCA, and clinical impact curves in the validation group to further validate the predictive model. If the predictive model performs well in the validation group, further draw a nomogram to demonstrate.<br/><strong>Results:</strong> This study extracted 19 imaging features from the chest CT scans of 75 patients downloaded from TCIA and finally selected 18 complete data for analysis. First, univariate analysis and multivariate analysis were performed, and a total of 5 variables were obtained: spicule, necrosis, air bronchogram Sign, atelectasis, pulmonary hilum and bronchial lymph nodes. After conducting modeling analysis with AUC = 0.887, a validation group was established using clinical cases from our hospital, Draw ROC curve with AUC = 0.865 in the validation group, evaluate the accuracy of the model through C","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"86 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Commonly, the thyroid gland is regarded as an organ with fewer metastatic diseases, and colorectal metastasis to the thyroid (CMT) is rarely reported, especially, with that the clinical sign of thyroid metastasis nidus is the chief complaint. The CMT occurs in advanced colorectal cancer and is associated with poor prognosis and short survival. Case Report: In this case, we reported a patient with the sign of neck mass as the first manifestation of CMT. The patient underwent a partial thyroidectomy in June 2019, immunohistochemical findings of thyroid carcinoma suggested the possibility of adenocarcinoma of gastrointestinal tract. The patient underwent a colonoscopy in July 2019 and a colonic mass was found. Pathological examination diagnosed rectal adenocarcinoma. The patient underwent neoadjuvant chemotherapy, surgical treatment, postoperative adjuvant chemotherapy and targeted therapy. The patient died in June 2022. Conclusion: The metastasis disease would not be ignored at all, when a patient complains at signs of neck mass. Further, the possibility of metastasis cancer should be considered once thyroid nodules occur in patients with colorectal cancer. Even though the biological characteristics and stage of the primary tumor have an important impact on the prognosis, positive standardized treatments can also be helpful.
{"title":"Sign of Neck Mass as the Chief Complaint: A Case Report and Literature Review About Thyroid Metastasis of Colorectal Cancer","authors":"Zhaorui Wang, Jingjing Wang, Jing Pei, Yubo Pan, Rui Ding","doi":"10.2147/cmar.s470045","DOIUrl":"https://doi.org/10.2147/cmar.s470045","url":null,"abstract":"<strong>Background:</strong> Commonly, the thyroid gland is regarded as an organ with fewer metastatic diseases, and colorectal metastasis to the thyroid (CMT) is rarely reported, especially, with that the clinical sign of thyroid metastasis nidus is the chief complaint. The CMT occurs in advanced colorectal cancer and is associated with poor prognosis and short survival.<br/><strong>Case Report:</strong> In this case, we reported a patient with the sign of neck mass as the first manifestation of CMT. The patient underwent a partial thyroidectomy in June 2019, immunohistochemical findings of thyroid carcinoma suggested the possibility of adenocarcinoma of gastrointestinal tract. The patient underwent a colonoscopy in July 2019 and a colonic mass was found. Pathological examination diagnosed rectal adenocarcinoma. The patient underwent neoadjuvant chemotherapy, surgical treatment, postoperative adjuvant chemotherapy and targeted therapy. The patient died in June 2022.<br/><strong>Conclusion:</strong> The metastasis disease would not be ignored at all, when a patient complains at signs of neck mass. Further, the possibility of metastasis cancer should be considered once thyroid nodules occur in patients with colorectal cancer. Even though the biological characteristics and stage of the primary tumor have an important impact on the prognosis, positive standardized treatments can also be helpful.<br/><br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"18 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: Engraftment syndrome (ES) is an early complication of hematopoietic stem cell transplantation (HSCT) characterized by fever and additional clinical manifestations including rash, diarrhea, lung infiltrates, weight gain, and neurological symptoms. Steroid-resistant ES following HSCT significantly affects the efficacy of transplantation and may even result in patient mortality. As ES essentially represents a cytokine storm induced by engrafted donor cells with interferon-gamma (IFN-γ) playing a central role, we hypothesized that emapalumab (an anti-IFN-γ monoclonal antibody) may be an effective approach to treat steroid-resistant ES. Here, we present a case report of a 14-year-old female patient who received a second haploidentical HSCT due to a relapse of acute myeloid leukemia. Nine days after the transplantation, the patient developed a fever and exhibited a poor response to antimicrobials (ceftazidime/avibactam). A few days later, the patient presented with a new-onset rash, weight gain, and impaired liver function, leading to a diagnosis of ES. Initial immunosuppressive (tacrolimus and mycophenolate mofetil) treatment failed to control the disease. On day 16 post-transplantation, the patient received two infusions of 50 mg of emapalumab. Following the initiation of emapalumab treatment, the patient’s fever returned to normal and ES was effectively controlled. This case report demonstrated that emapalumab had a possible efficacy for steroid-resistant ES and provided a novel therapeutic strategy to treat this clinical complication.
摘要：移植综合征（ES）是造血干细胞移植（HSCT）的早期并发症，以发热和其他临床表现（包括皮疹、腹泻、肺部浸润、体重增加和神经系统症状）为特征。造血干细胞移植后的类固醇耐药ES会严重影响移植效果，甚至可能导致患者死亡。由于 ES 本质上是由移植供体细胞诱导的细胞因子风暴，其中干扰素-γ（IFN-γ）起着核心作用，因此我们假设埃马帕鲁单抗（一种抗 IFN-γ 的单克隆抗体）可能是治疗类固醇耐药 ES 的有效方法。在此，我们报告了一例因急性髓性白血病复发而接受第二次单倍体造血干细胞移植的 14 岁女性患者的病例。移植九天后，患者出现发热，对抗菌药物（头孢唑肟/阿维菌素）反应不佳。几天后，患者出现新发皮疹、体重增加和肝功能受损，最终被诊断为 ES。最初的免疫抑制（他克莫司和霉酚酸酯）治疗未能控制病情。移植后第16天，患者接受了两次50毫克的伊马单抗输注。开始接受伊马帕鲁单抗治疗后，患者的发热恢复正常，ES也得到了有效控制。本病例报告表明，依马单抗对类固醇耐药的ES可能有疗效，并为治疗这一临床并发症提供了一种新的治疗策略。 关键词：单倍体造血干细胞移植；移植综合征；依马单抗；急性髓性白血病
{"title":"Successful Treatment of Severe Steroid-Resistant Engraftment Syndrome Following Haploidentical Allogeneic Hematopoietic Stem Cell Transplantation for Acute Myeloid Leukemia with Emapalumab: A Case Report","authors":"Zhengqin Tian, Qihang Man, Yixin Yang, Xiaomei Zhang, Hexian Guan, Wenjing Gu, Ying Wang, Dandan Song, Rongmu Luo, Jingbo Wang","doi":"10.2147/cmar.s458577","DOIUrl":"https://doi.org/10.2147/cmar.s458577","url":null,"abstract":"<strong>Abstract:</strong> Engraftment syndrome (ES) is an early complication of hematopoietic stem cell transplantation (HSCT) characterized by fever and additional clinical manifestations including rash, diarrhea, lung infiltrates, weight gain, and neurological symptoms. Steroid-resistant ES following HSCT significantly affects the efficacy of transplantation and may even result in patient mortality. As ES essentially represents a cytokine storm induced by engrafted donor cells with interferon-gamma (IFN-γ) playing a central role, we hypothesized that emapalumab (an anti-IFN-γ monoclonal antibody) may be an effective approach to treat steroid-resistant ES. Here, we present a case report of a 14-year-old female patient who received a second haploidentical HSCT due to a relapse of acute myeloid leukemia. Nine days after the transplantation, the patient developed a fever and exhibited a poor response to antimicrobials (ceftazidime/avibactam). A few days later, the patient presented with a new-onset rash, weight gain, and impaired liver function, leading to a diagnosis of ES. Initial immunosuppressive (tacrolimus and mycophenolate mofetil) treatment failed to control the disease. On day 16 post-transplantation, the patient received two infusions of 50 mg of emapalumab. Following the initiation of emapalumab treatment, the patient’s fever returned to normal and ES was effectively controlled. This case report demonstrated that emapalumab had a possible efficacy for steroid-resistant ES and provided a novel therapeutic strategy to treat this clinical complication.<br/><br/><strong>Keywords:</strong> haploidentical hematopoietic stem cell transplantation, engraftment syndrome, emapalumab, acute myeloid leukemia<br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"68 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141253037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Youren Dai, Huiyun Wu, Jiahui Cao, Yang Li, Wenjun Cheng, Chengyan Luo
Purpose: To investigate prognostic factors affecting cancer-specific survival (CSS) and to analyze the survival outcomes of patients with undifferentiated and dedifferentiated endometrial carcinoma (UDEC) who underwent various postoperative adjuvant therapies. Methods: The independent risk factors affecting CSS were studied using univariate and multivariate Cox regression analysis, and CSS in the presence of various postoperative treatments was evaluated using Kaplan-Meier method based on the cohort with pathologically confirmed UDEC from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, the study included 18 cases with UDEC in our center and explored their molecular characteristics and prognosis. Results: Between 2000 and 2019, a total of 443 patients were included from the SEER database. The median CSS duration was 14 months, with corresponding 3- and 5-year CSS rates of 45.9% and 44.0%, respectively. Factors such as pTNM stage, surgical resection of primary lesion, and chemoradiation independently influenced CSS. Postoperative chemotherapy alone improved CSS in patients with initial tumor spread beyond the uterus (pT3 and pT4), or lymph node (LN) invasion, or distant metastases. Additionally, postoperative radiotherapy enhanced CSS in patients who had undergone postoperative chemotherapy, those with primary tumors progressing to stage pT3, and those with LN involvement but without distant metastases. Of the 18 patients diagnosed at our center, with a median follow-up of 15.5 months, one experienced relapse and two succumbed to UDEC, who exhibited aberrant p53 expression in immunohistochemical staining. Conclusion: Postoperative chemotherapy and radiotherapy are beneficial for UDEC patients with tumors extending beyond the uterus or involving lymph nodes.
{"title":"Analysis of Prognostic Factors and Cancer-Specific Survival in Patients with Undifferentiated and Dedifferentiated Endometrial Carcinoma Undergoing Various Postoperative Adjuvant Therapies","authors":"Youren Dai, Huiyun Wu, Jiahui Cao, Yang Li, Wenjun Cheng, Chengyan Luo","doi":"10.2147/cmar.s466022","DOIUrl":"https://doi.org/10.2147/cmar.s466022","url":null,"abstract":"<strong>Purpose:</strong> To investigate prognostic factors affecting cancer-specific survival (CSS) and to analyze the survival outcomes of patients with undifferentiated and dedifferentiated endometrial carcinoma (UDEC) who underwent various postoperative adjuvant therapies.<br/><strong>Methods:</strong> The independent risk factors affecting CSS were studied using univariate and multivariate Cox regression analysis, and CSS in the presence of various postoperative treatments was evaluated using Kaplan-Meier method based on the cohort with pathologically confirmed UDEC from the Surveillance, Epidemiology, and End Results (SEER) database. Meanwhile, the study included 18 cases with UDEC in our center and explored their molecular characteristics and prognosis.<br/><strong>Results:</strong> Between 2000 and 2019, a total of 443 patients were included from the SEER database. The median CSS duration was 14 months, with corresponding 3- and 5-year CSS rates of 45.9% and 44.0%, respectively. Factors such as pTNM stage, surgical resection of primary lesion, and chemoradiation independently influenced CSS. Postoperative chemotherapy alone improved CSS in patients with initial tumor spread beyond the uterus (pT3 and pT4), or lymph node (LN) invasion, or distant metastases. Additionally, postoperative radiotherapy enhanced CSS in patients who had undergone postoperative chemotherapy, those with primary tumors progressing to stage pT3, and those with LN involvement but without distant metastases. Of the 18 patients diagnosed at our center, with a median follow-up of 15.5 months, one experienced relapse and two succumbed to UDEC, who exhibited aberrant p53 expression in immunohistochemical staining.<br/><strong>Conclusion:</strong> Postoperative chemotherapy and radiotherapy are beneficial for UDEC patients with tumors extending beyond the uterus or involving lymph nodes.<br/><br/><strong>Keywords:</strong> undifferentiated and dedifferentiated endometrial carcinoma, cancer-specific survival, prognostic factors, postoperative adjuvant therapy<br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"2013 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141252744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: Recurrence is the main factor for poor prognosis of bladder cancer. Therefore, it is necessary to develop new biomarkers to predict the prognosis of bladder cancer. In this study, we used machine learning (ML) methods based on a variety of clinical variables to screen prognostic biomarkers of bladder cancer. Patients and Methods: A total of 345 bladder cancer patients were participated in this retrospective study and randomly divided into training and testing group. We used five supervised clustering ML algorithms: decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) to obtained prediction information through 34 clinical parameters. Results: By comparing five ML algorithms, we found that total bilirubin (TBIL) and CA50 had the best performance in predicting the recurrence of bladder cancer. In addition, the combined predictive performance of the two is superior to the performance of any single indicator prediction. Conclusion: ML technology can evaluate the recurrence of bladder cancer. This study shows that the combination of TBIL and CA50 can improve the prognosis prediction of bladder cancer recurrence, which can help clinicians make decisions and develop personalized treatment strategies.
Keywords: bladder cancer, recurrence, machine learning, biomarkers, retrospective study
{"title":"Predictive Value of the Total Bilirubin and CA50 Screened Based on Machine Learning for Recurrence of Bladder Cancer Patients","authors":"Xiaosong Zhang, Limin Ma","doi":"10.2147/cmar.s457269","DOIUrl":"https://doi.org/10.2147/cmar.s457269","url":null,"abstract":"<strong>Purpose:</strong> Recurrence is the main factor for poor prognosis of bladder cancer. Therefore, it is necessary to develop new biomarkers to predict the prognosis of bladder cancer. In this study, we used machine learning (ML) methods based on a variety of clinical variables to screen prognostic biomarkers of bladder cancer.<br/><strong>Patients and Methods:</strong> A total of 345 bladder cancer patients were participated in this retrospective study and randomly divided into training and testing group. We used five supervised clustering ML algorithms: decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) to obtained prediction information through 34 clinical parameters.<br/><strong>Results:</strong> By comparing five ML algorithms, we found that total bilirubin (TBIL) and CA50 had the best performance in predicting the recurrence of bladder cancer. In addition, the combined predictive performance of the two is superior to the performance of any single indicator prediction.<br/><strong>Conclusion:</strong> ML technology can evaluate the recurrence of bladder cancer. This study shows that the combination of TBIL and CA50 can improve the prognosis prediction of bladder cancer recurrence, which can help clinicians make decisions and develop personalized treatment strategies.<br/><br/><strong>Keywords:</strong> bladder cancer, recurrence, machine learning, biomarkers, retrospective study<br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"39 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141193647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: The aim of this study was to evaluate the potential benefit of blood inflammation in the diagnosis of non-small cell lung cancer (NSCLC) and propose a machine-learning-based method to predict NSCLC in asymptomatic adults. Patients and Methods: A cross-sectional study was evaluated using medical records of 139 patients with non-small cell lung cancer and physical examination data from May 2022 to May 2023 of 198 healthy controls. The NSCLC cohort comprised 128 cases of adenocarcinoma, 3 cases of squamous cell carcinoma, and 8 cases of other NSCLC subtypes. The correlation between inflammatory and nutritional markers, such as monocytes, neutrophils, LMR, NLR, PLR, PHR and non-small cell lung cancer was examined. Features were selected using Python’s feature selection library and analyzed by five algorithms. The predictive ability of the model for non-small cell lung cancer diagnosis was assessed by precision, accuracy, recall, F1 score, and area under the curve (AUC). Results: The results showed that the top 14 important factors were PDW, age, TP, RBC, HGB, LYM, LYM%, RDW, PLR, LMR, PHR, MONO, MONO%, gender. Additionally, the naive Bayes (NB) algorithm demonstrated the highest overall performance in predicting adult NSCLC among the five machine learning algorithms, achieving an accuracy of 0.87, a macro average F1 score of 0.85, a weighted average F1 score of 0.87, and an AUC of 0.84. Conclusion: In feature ranking, platelet distribution width was the most important feature, and the NB algorithm performed best in predicting adult NSCLC diagnosis.
目的：本研究旨在评估血液炎症对诊断非小细胞肺癌（NSCLC）的潜在益处，并提出一种基于机器学习的方法来预测无症状成年人的NSCLC：利用139名非小细胞肺癌患者的医疗记录和198名健康对照者2022年5月至2023年5月的体检数据，对一项横断面研究进行了评估。非小细胞肺癌队列包括128例腺癌、3例鳞状细胞癌和8例其他非小细胞肺癌亚型。研究人员检测了单核细胞、中性粒细胞、LMR、NLR、PLR、PHR 等炎症和营养标记物与非小细胞肺癌之间的相关性。使用 Python 的特征选择库选择特征，并通过五种算法进行分析。模型对非小细胞肺癌诊断的预测能力通过精确度、准确度、召回率、F1得分和曲线下面积（AUC）进行评估：结果显示，排在前14位的重要因素分别是PDW、年龄、TP、RBC、HGB、LYM、LYM%、RDW、PLR、LMR、PHR、MONO、MONO%、性别。此外，在五种机器学习算法中，天真贝叶斯（NB）算法在预测成人 NSCLC 方面的总体性能最高，准确率达到 0.87，宏观平均 F1 得分为 0.85，加权平均 F1 得分为 0.87，AUC 为 0.84：关键词：机器学习；非小细胞肺癌；炎症指标；营养指标；比值；诊断
{"title":"Machine Learning for Prediction of Non-Small Cell Lung Cancer Based on Inflammatory and Nutritional Indicators in Adults: A Cross-Sectional Study","authors":"Qiaoli Wang, Tao Liang, Yuexi Li, Xiaoqin Liu","doi":"10.2147/cmar.s454638","DOIUrl":"https://doi.org/10.2147/cmar.s454638","url":null,"abstract":"<strong>Purpose:</strong> The aim of this study was to evaluate the potential benefit of blood inflammation in the diagnosis of non-small cell lung cancer (NSCLC) and propose a machine-learning-based method to predict NSCLC in asymptomatic adults.<br/><strong>Patients and Methods:</strong> A cross-sectional study was evaluated using medical records of 139 patients with non-small cell lung cancer and physical examination data from May 2022 to May 2023 of 198 healthy controls. The NSCLC cohort comprised 128 cases of adenocarcinoma, 3 cases of squamous cell carcinoma, and 8 cases of other NSCLC subtypes. The correlation between inflammatory and nutritional markers, such as monocytes, neutrophils, LMR, NLR, PLR, PHR and non-small cell lung cancer was examined. Features were selected using Python’s feature selection library and analyzed by five algorithms. The predictive ability of the model for non-small cell lung cancer diagnosis was assessed by precision, accuracy, recall, F1 score, and area under the curve (AUC).<br/><strong>Results:</strong> The results showed that the top 14 important factors were PDW, age, TP, RBC, HGB, LYM, LYM%, RDW, PLR, LMR, PHR, MONO, MONO%, gender. Additionally, the naive Bayes (NB) algorithm demonstrated the highest overall performance in predicting adult NSCLC among the five machine learning algorithms, achieving an accuracy of 0.87, a macro average F1 score of 0.85, a weighted average F1 score of 0.87, and an AUC of 0.84.<br/><strong>Conclusion:</strong> In feature ranking, platelet distribution width was the most important feature, and the NB algorithm performed best in predicting adult NSCLC diagnosis.<br/><br/><strong>Keywords:</strong> machine learning, non-small cell lung cancer, inflammatory indicators, nutritional indicators, ratio, diagnosis<br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"36 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141193427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seunghee Bae, Sowon Bae, Hee Su Kim, Ye Jin Lim, Gyeongmi Kim, In-Chul Park, Kyeong A So, Tae Jin Kim, Jae Ho Lee
Background: Ovarian cancer is one of women’s malignancies with the highest mortality among gynecological cancers. Paclitaxel is used in first-line ovarian cancer chemotherapy. Research on paclitaxel-resistant ovarian cancer holds significant clinical importance. Methods: Cell viability and flow cytometric assays were conducted at different time and concentration points of deguelin and paclitaxel treatment. Immunoblotting was performed to assess the activation status of key signaling molecules important for cell survival and proliferation following treatment with deguelin and paclitaxel. The fluo-3 acetoxymethyl assay for P-glycoprotein transport activity assay and cell viability assay in the presence of N-acetyl-L-cysteine were also conducted. Results: Cell viability and flow cytometric assays demonstrated that deguelin resensitized paclitaxel in a dose- and time-dependent manner. Cotreatment with deguelin and paclitaxel inhibited EGFR and its downstream signaling molecules, including AKT, ERK, STAT3, and p38 MAPK, in SKOV3-TR cells. Interestingly, cotreatment with deguelin and paclitaxel suppressed the expression level of EGFR via the lysosomal degradation pathway. Cotreatment did not affect the expression and function of P-glycoprotein. N-acetyl-L-cysteine failed to restore cell cytotoxicity when used in combination with deguelin and paclitaxel in SKOV3-TR cells. The expression of BCL-2, MCL-1, and the phosphorylation of the S155 residue of BAD were downregulated. Moreover, inhibition of paclitaxel resistance by deguelin was also observed in HeyA8-MDR cells. Conclusion: Our research showed that deguelin effectively suppresses paclitaxel resistance in SKOV3-TR ovarian cancer cells by downregulating the EGFR and its downstream signaling pathway and modulating the BCL-2 family proteins. Furthermore, deguelin exhibits inhibitory effects on paclitaxel resistance in HeyA8-MDR ovarian cancer cells, suggesting a potential mechanism for paclitaxel resensitization that may not be cell-specific. These findings suggest that deguelin holds promise as an anticancer therapeutic agent for overcoming chemoresistance in ovarian cancer.
{"title":"Deguelin Restores Paclitaxel Sensitivity in Paclitaxel-Resistant Ovarian Cancer Cells via Inhibition of the EGFR Signaling Pathway","authors":"Seunghee Bae, Sowon Bae, Hee Su Kim, Ye Jin Lim, Gyeongmi Kim, In-Chul Park, Kyeong A So, Tae Jin Kim, Jae Ho Lee","doi":"10.2147/cmar.s457221","DOIUrl":"https://doi.org/10.2147/cmar.s457221","url":null,"abstract":"<strong>Background:</strong> Ovarian cancer is one of women’s malignancies with the highest mortality among gynecological cancers. Paclitaxel is used in first-line ovarian cancer chemotherapy. Research on paclitaxel-resistant ovarian cancer holds significant clinical importance.<br/><strong>Methods:</strong> Cell viability and flow cytometric assays were conducted at different time and concentration points of deguelin and paclitaxel treatment. Immunoblotting was performed to assess the activation status of key signaling molecules important for cell survival and proliferation following treatment with deguelin and paclitaxel. The fluo-3 acetoxymethyl assay for P-glycoprotein transport activity assay and cell viability assay in the presence of N-acetyl-L-cysteine were also conducted.<br/><strong>Results:</strong> Cell viability and flow cytometric assays demonstrated that deguelin resensitized paclitaxel in a dose- and time-dependent manner. Cotreatment with deguelin and paclitaxel inhibited EGFR and its downstream signaling molecules, including AKT, ERK, STAT3, and p38 MAPK, in SKOV3-TR cells. Interestingly, cotreatment with deguelin and paclitaxel suppressed the expression level of EGFR via the lysosomal degradation pathway. Cotreatment did not affect the expression and function of P-glycoprotein. N-acetyl-L-cysteine failed to restore cell cytotoxicity when used in combination with deguelin and paclitaxel in SKOV3-TR cells. The expression of BCL-2, MCL-1, and the phosphorylation of the S155 residue of BAD were downregulated. Moreover, inhibition of paclitaxel resistance by deguelin was also observed in HeyA8-MDR cells.<br/><strong>Conclusion:</strong> Our research showed that deguelin effectively suppresses paclitaxel resistance in SKOV3-TR ovarian cancer cells by downregulating the EGFR and its downstream signaling pathway and modulating the BCL-2 family proteins. Furthermore, deguelin exhibits inhibitory effects on paclitaxel resistance in HeyA8-MDR ovarian cancer cells, suggesting a potential mechanism for paclitaxel resensitization that may not be cell-specific. These findings suggest that deguelin holds promise as an anticancer therapeutic agent for overcoming chemoresistance in ovarian cancer. <br/><br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"38 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141170089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jie-Yu Zhou, Cheng-Geng Pan, Yang Ye, Zhi-Wei Li, Wei-Da Fu, Bin-Hao Jiang
Purpose: We aimed to develop a nomogram to predict prognosis of HR+ HER2- breast cancer patients and guide the application of postoperative adjuvant chemotherapy. Methods: We identified 310 eligible HR+ HER- breast cancer patients and randomly divided the database into a training group and a validation group. The endpoint was disease free survival (DFS). Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluate predictive accuracy and discriminative ability of the nomogram. We also compared the predictive accuracy and discriminative ability of our nomogram with the eighth AJCC staging system using overall data. Results: According to the training group, platelet-to-lymphocyte ratio (PLR), tumor size, positive lymph nodes and Ki-67 index were used to construct the nomogram of DFS. The C-index of DFS was 0.708 (95% CI: 0.623– 0.793) in the training group and 0.67 (95% CI: 0.544– 0.796) in the validation group. The calibration curves revealed great consistencies in both groups. Conclusion: We have developed and validated a novel and practical nomogram that can provide individual prediction of DFS for patients with HR+ HER- breast cancer. This nomogram may help clinicians in risk consulting and guiding the application of postoperative adjuvant chemotherapy.
Keywords: nomograms, prognosis, prediction, HR+ HER- breast cancer, chemotherapy
{"title":"Development and Validation of a Prognostic Nomogram for HR+ HER- Breast Cancer","authors":"Jie-Yu Zhou, Cheng-Geng Pan, Yang Ye, Zhi-Wei Li, Wei-Da Fu, Bin-Hao Jiang","doi":"10.2147/cmar.s459714","DOIUrl":"https://doi.org/10.2147/cmar.s459714","url":null,"abstract":"<strong>Purpose:</strong> We aimed to develop a nomogram to predict prognosis of HR+ HER2- breast cancer patients and guide the application of postoperative adjuvant chemotherapy.<br/><strong>Methods:</strong> We identified 310 eligible HR+ HER- breast cancer patients and randomly divided the database into a training group and a validation group. The endpoint was disease free survival (DFS). Concordance index (C-index), area under the curve (AUC) and calibration curves were used to evaluate predictive accuracy and discriminative ability of the nomogram. We also compared the predictive accuracy and discriminative ability of our nomogram with the eighth AJCC staging system using overall data.<br/><strong>Results:</strong> According to the training group, platelet-to-lymphocyte ratio (PLR), tumor size, positive lymph nodes and Ki-67 index were used to construct the nomogram of DFS. The C-index of DFS was 0.708 (95% CI: 0.623– 0.793) in the training group and 0.67 (95% CI: 0.544– 0.796) in the validation group. The calibration curves revealed great consistencies in both groups.<br/><strong>Conclusion:</strong> We have developed and validated a novel and practical nomogram that can provide individual prediction of DFS for patients with HR+ HER- breast cancer. This nomogram may help clinicians in risk consulting and guiding the application of postoperative adjuvant chemotherapy.<br/><br/><strong>Keywords:</strong> nomograms, prognosis, prediction, HR+ HER- breast cancer, chemotherapy<br/>","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"35 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141151687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Retraction for the article Overexpression of chloride channel-3 predicts unfavorable prognosis and promotes cellular invasion in gastric cancer
撤回文章 氯离子通道-3的过度表达预示着胃癌的不良预后并促进细胞侵袭
{"title":"Overexpression of Chloride Channel-3 Predicts Unfavorable Prognosis and Promotes Cellular Invasion in Gastric Cancer [Retraction]","authors":"Jianjun Peng, Wei Chen, Jianhui Chen, Yujie Yuan, Jian Zhang, Yulong He","doi":"10.2147/cmar.s478202","DOIUrl":"https://doi.org/10.2147/cmar.s478202","url":null,"abstract":"Retraction for the article Overexpression of chloride channel-3 predicts unfavorable prognosis and promotes cellular invasion in gastric cancer","PeriodicalId":9479,"journal":{"name":"Cancer Management and Research","volume":"44 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141063671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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