Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.96
H. Belhadj-Tahar, Jindde Chen, P. Song, Jun Zhao, M. Quan, Caixin Li, Xingjian Gu, Guanghua Yang, Yong Gao
96 Background: Stereotactic brachytherapy for extensive local tumors offers a very effective treatment option locally without significant complications in medically impaired patients. In this context, we have recently developed a new potential anticancer agent from Poly-L-Lysins dendrimer as a delivery nano system loaded with diffusible Imidazolic probes complexed with 188-Rhenium for targeting in particular hypoxic tumors resistant to conventional cancer treatments. The aim of the study is assessment the safety profile and therapeutic efficacy of anticancer agent derived from [188Re]rhenium-ligand as radioactive ligand loaded 5th generation poly-L-lysine dendrimer in patients with unresectable Lung Malignancies. Methods: The experiment agent “ 188Re-ImDendrim” is consisting of 5th generation poly-L-lysine dendrimer (20 nM) mixed with nitro-imidazole-methyl-1,2,3-triazol-methyl-di-(2-pycolyl) amine at GMP grade and labelled with [188Re]-rhenium. The study was approved by Shanghai East Hospital ethics committee. 5 patients received “188Re-ImDendrim” directly into lung tumors under CT-guidance, at an activity level of 162 MBq/cc of tumor (range 2 to 7 cm; mean diameter, 4 cm) . For voluminous tumors ( > 65 cc) the dose is given in divided injection spaced 2 weeks apart (Tumor of 115cc: 2 administrations, Tumor of 180 cc: 3 administrations). At H0.5, H 4, H24, H36 , H72 post-administration, the patient get a SPECT control. The response to treatment is evaluated thanks to PET/CT Standardized Uptake Values (SUVs). Results: Stereotactic administrations of “188-Rhenium-ImDendrim” were successfully carried out in all patients under local anesthesia. The radioactive product diffuses homogeneously in the tumor volume and remains 72 hours post-administration with no significant diffusion out site of injection. The One of the 5 patients reported discrete transitive hemoptysis as adverse events. All targeted tumors were responding at 12 weeks, with two complete responses. Conclusions: Percutaneous single and iterative administrations of this novel 188-Rhenium-Imdendrim brachytherapy device into lung cancers are safe and well tolerated. The initial data on therapeutic response are promising. Clinical trial information: EC.D (BG) 016.03.1.
{"title":"Novel CT-guided 188-rhenium brachytherapy device for local primary and secondary lung malignancies.","authors":"H. Belhadj-Tahar, Jindde Chen, P. Song, Jun Zhao, M. Quan, Caixin Li, Xingjian Gu, Guanghua Yang, Yong Gao","doi":"10.1200/jgo.2019.5.suppl.96","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.96","url":null,"abstract":"96 Background: Stereotactic brachytherapy for extensive local tumors offers a very effective treatment option locally without significant complications in medically impaired patients. In this context, we have recently developed a new potential anticancer agent from Poly-L-Lysins dendrimer as a delivery nano system loaded with diffusible Imidazolic probes complexed with 188-Rhenium for targeting in particular hypoxic tumors resistant to conventional cancer treatments. The aim of the study is assessment the safety profile and therapeutic efficacy of anticancer agent derived from [188Re]rhenium-ligand as radioactive ligand loaded 5th generation poly-L-lysine dendrimer in patients with unresectable Lung Malignancies. Methods: The experiment agent “ 188Re-ImDendrim” is consisting of 5th generation poly-L-lysine dendrimer (20 nM) mixed with nitro-imidazole-methyl-1,2,3-triazol-methyl-di-(2-pycolyl) amine at GMP grade and labelled with [188Re]-rhenium. The study was approved by Shanghai East Hospital ethics committee. 5 patients received “188Re-ImDendrim” directly into lung tumors under CT-guidance, at an activity level of 162 MBq/cc of tumor (range 2 to 7 cm; mean diameter, 4 cm) . For voluminous tumors ( > 65 cc) the dose is given in divided injection spaced 2 weeks apart (Tumor of 115cc: 2 administrations, Tumor of 180 cc: 3 administrations). At H0.5, H 4, H24, H36 , H72 post-administration, the patient get a SPECT control. The response to treatment is evaluated thanks to PET/CT Standardized Uptake Values (SUVs). Results: Stereotactic administrations of “188-Rhenium-ImDendrim” were successfully carried out in all patients under local anesthesia. The radioactive product diffuses homogeneously in the tumor volume and remains 72 hours post-administration with no significant diffusion out site of injection. The One of the 5 patients reported discrete transitive hemoptysis as adverse events. All targeted tumors were responding at 12 weeks, with two complete responses. Conclusions: Percutaneous single and iterative administrations of this novel 188-Rhenium-Imdendrim brachytherapy device into lung cancers are safe and well tolerated. The initial data on therapeutic response are promising. Clinical trial information: EC.D (BG) 016.03.1.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41344584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.91
Tran Duc Canh, Bui Anh Tuyet, P. Dat, Nguyen Van Chu
91 Background: Gastric cancer is in the top three most common cancers in Vietnam and the disease is mainly detected in late stage. There is a lack of evaluation of the pre-neoplasia stage of gastric cancer and selection an appropriate and effective treatment remains still in debate. Hence, the study aims to evaluate, for the first time, the safety and efficacy of the application of endoscopic submucosal dissection (ESD) technique on Vietnamese patients with pre-neoplasia lesion in stomach. Methods: We included all patients diagnosed with lower or high-grade gastric dysplasia and hopitalized in the Department of Endoscopic and Functional Exploration in K Hospital from March 2018 to June 2019. Eligible patients were applied by the ESD technique as the standard treatment. We evaluated the efficacy and safety of after the intervention of ESD by the neoplasia recurrence rate after 3 months and the occurrence of adverse events during and after the ESD procedure described in frequency and percentage. Results: During the investigational period, we chose 65 pre-neoplasia gastric patients for the application of ESD technique. The male/female ratio was 1.09 and the mean age of patients was 58.07 years. The duration of hospitalization was about 3 days. We found 57 patients (87.69%) with location of the lesions in pylorus. The average of tumor sizes was 20.46 mm. All patients were treated with curative en bloc resection and no case was found as failure. Out of 65 patients, we found 2 patients (3%) with bleeding complication, no perforation and other post-surgery complication were identified. The average of procedure time was short (67.53 minutes). The histopathological specimen results revealed that 20 patients (30.76%) were diagnosed as cancer and 40 patients (61.53%) were diagnosed as high-grade dysplasia, all patients had a margin negative after ESD. After 3 months of treatment, all patients have no pre-neoplastic recurrence. Conclusions: Our result showed that the ESD technique is relatively safe and effective for Vietnamese patients with pre-neoplasia at stomach.
{"title":"Preliminary results of endoscopic submucosal dissection in Vietnamese patients with gastric pre-neoplasia lesion.","authors":"Tran Duc Canh, Bui Anh Tuyet, P. Dat, Nguyen Van Chu","doi":"10.1200/jgo.2019.5.suppl.91","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.91","url":null,"abstract":"91 Background: Gastric cancer is in the top three most common cancers in Vietnam and the disease is mainly detected in late stage. There is a lack of evaluation of the pre-neoplasia stage of gastric cancer and selection an appropriate and effective treatment remains still in debate. Hence, the study aims to evaluate, for the first time, the safety and efficacy of the application of endoscopic submucosal dissection (ESD) technique on Vietnamese patients with pre-neoplasia lesion in stomach. Methods: We included all patients diagnosed with lower or high-grade gastric dysplasia and hopitalized in the Department of Endoscopic and Functional Exploration in K Hospital from March 2018 to June 2019. Eligible patients were applied by the ESD technique as the standard treatment. We evaluated the efficacy and safety of after the intervention of ESD by the neoplasia recurrence rate after 3 months and the occurrence of adverse events during and after the ESD procedure described in frequency and percentage. Results: During the investigational period, we chose 65 pre-neoplasia gastric patients for the application of ESD technique. The male/female ratio was 1.09 and the mean age of patients was 58.07 years. The duration of hospitalization was about 3 days. We found 57 patients (87.69%) with location of the lesions in pylorus. The average of tumor sizes was 20.46 mm. All patients were treated with curative en bloc resection and no case was found as failure. Out of 65 patients, we found 2 patients (3%) with bleeding complication, no perforation and other post-surgery complication were identified. The average of procedure time was short (67.53 minutes). The histopathological specimen results revealed that 20 patients (30.76%) were diagnosed as cancer and 40 patients (61.53%) were diagnosed as high-grade dysplasia, all patients had a margin negative after ESD. After 3 months of treatment, all patients have no pre-neoplastic recurrence. Conclusions: Our result showed that the ESD technique is relatively safe and effective for Vietnamese patients with pre-neoplasia at stomach.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41514548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.118
Jie Xu, Lu Xie, W. Guo, Xin Sun, Kuisheng Liu, Bingxin Zheng, T. Ren, Yi Huang, Xiaodong Tang, T. Yan, Rongli Yang
118 Background: Both protracted irinotecan and anti-angiogenesis therapy have shown promising results in Ewing sarcoma. We did this phase Ib/II trial to first define the proper dose of irinotecan in combination with anlotinib in Ewing sarcoma (phase Ib) and then evaluate efficacy (phase II). Methods: Patients diagnosed with recurrent or refractory Ewing sarcoma were enrolled and sub-classified into cohort A (≥16y) or cohort B ( < 16y). In the dose-defining phase Ib portion, anlotinib was given at a fixed dose of 12mg D1-14 every 21 days, while the de-escalated 3+3 design was used to detect the recommended dose of irinotecan in each cohort from an initial level of 20mg/m2/d dx5x2. Recommended phase 2 dose (RP2D) was defined as the highest dose at which no more than 30% patients experience a DLT in the first two courses. In the next dose-expanding phase II portion, the primary endpoint was objective response rate at 12 weeks (ORR12w). Results: 41 patients were finally enrolled with 29 in cohortA and 12 in cohortB. For cohortA, first 5 patients were treated at initial level in phase Ib portion, two of whom subsequently experienced delayed diarrhea as dose-limiting toxicity (DLT). Additional six patients were then treated at a lower dose of 15mg/m2. Since no more DLT was recorded, it was used as RP2D. 23/24 patients in cohort A phase II were available for response evaluation at 12 weeks, with one complete response (CR), 14 partial response (PR) , 2 stable disease (SD) and 6 progressive disease (PD). ORR12wwas 62.5%. For cohort B, no DLT was noticed in the first six patients treated at the initial level which was used as RP2D later. Finally, 12 patients were included in cohort B. ORR12wwas 83.3% with two CR, 8 PR and two PD. Although effective, cohort B were closed because of slow enrollment. Most common grade 3/4 adverse events were leukopenia (28.5%), neutropenia (24.4%), anemia (8.7%) and diarrhea (3.7%). The genotype of UGT1A1*1 and UGT1A1*28 were not associated with the risk of diarrhea. Conclusions: The combination of irinotecan and anlotinib demonstrated an acceptable toxicity profile with promising evidence of clinical efficacy in advanced Ewing sarcoma. Clinical trial information: NCT03416517.
{"title":"Anlotinib, vincristine, and irinotecan for advanced Ewing sarcoma after failure of standard multimodal therapy: A multicenter, two-cohort, phase Ib/II trial (NCT03416517).","authors":"Jie Xu, Lu Xie, W. Guo, Xin Sun, Kuisheng Liu, Bingxin Zheng, T. Ren, Yi Huang, Xiaodong Tang, T. Yan, Rongli Yang","doi":"10.1200/jgo.2019.5.suppl.118","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.118","url":null,"abstract":"118 Background: Both protracted irinotecan and anti-angiogenesis therapy have shown promising results in Ewing sarcoma. We did this phase Ib/II trial to first define the proper dose of irinotecan in combination with anlotinib in Ewing sarcoma (phase Ib) and then evaluate efficacy (phase II). Methods: Patients diagnosed with recurrent or refractory Ewing sarcoma were enrolled and sub-classified into cohort A (≥16y) or cohort B ( < 16y). In the dose-defining phase Ib portion, anlotinib was given at a fixed dose of 12mg D1-14 every 21 days, while the de-escalated 3+3 design was used to detect the recommended dose of irinotecan in each cohort from an initial level of 20mg/m2/d dx5x2. Recommended phase 2 dose (RP2D) was defined as the highest dose at which no more than 30% patients experience a DLT in the first two courses. In the next dose-expanding phase II portion, the primary endpoint was objective response rate at 12 weeks (ORR12w). Results: 41 patients were finally enrolled with 29 in cohortA and 12 in cohortB. For cohortA, first 5 patients were treated at initial level in phase Ib portion, two of whom subsequently experienced delayed diarrhea as dose-limiting toxicity (DLT). Additional six patients were then treated at a lower dose of 15mg/m2. Since no more DLT was recorded, it was used as RP2D. 23/24 patients in cohort A phase II were available for response evaluation at 12 weeks, with one complete response (CR), 14 partial response (PR) , 2 stable disease (SD) and 6 progressive disease (PD). ORR12wwas 62.5%. For cohort B, no DLT was noticed in the first six patients treated at the initial level which was used as RP2D later. Finally, 12 patients were included in cohort B. ORR12wwas 83.3% with two CR, 8 PR and two PD. Although effective, cohort B were closed because of slow enrollment. Most common grade 3/4 adverse events were leukopenia (28.5%), neutropenia (24.4%), anemia (8.7%) and diarrhea (3.7%). The genotype of UGT1A1*1 and UGT1A1*28 were not associated with the risk of diarrhea. Conclusions: The combination of irinotecan and anlotinib demonstrated an acceptable toxicity profile with promising evidence of clinical efficacy in advanced Ewing sarcoma. Clinical trial information: NCT03416517.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41489644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.49
C. French, D. Kurbegov, D. Spigel, M. Makowski, Samantha R. Terker, P. Clark
49 Background: Pulmonary nodule incidental findings challenge providers to balance resource efficiency and high clinical quality. Incidental findings tend to be under evaluated with studies reporting appropriate follow-up rates as low as 29%. The efficient identification of patients with high risk nodules is foundational to ensuring appropriate follow-up and requires the clinical reading and classification of radiology reports. We tested the feasibility of automating this process with natural language processing (NLP) and machine learning (ML). Methods: In cooperation with Sarah Cannon, the Cancer Institute of HCA Healthcare, we conducted a series of experiments on 8,879 free-text, narrative CT radiology reports. A representative sample of health system ED, IP, and OP reports dated from Dec 2015 - April 2017 were divided into a development set for model training and validation, and a test set to evaluate model performance. A “Nodule Model” was trained to detect the reported presence of a pulmonary nodule and a rules-based “Size Model” was developed to extract the size of the nodule in mms. Reports were bucketed into three prediction groups: ≥ 6 mm, <6 mm, and no size indicated. Nodules were placed in a queue for follow-up if the nodule was predicted ≥ 6 mm, or if the nodule had no size indicated and the report contained the word “mass.” The Fleischner Society Guidelines and clinical review informed these definitions. Results: Precision and recall metrics were calculated for multiple model thresholds. A threshold was selected based on the validation set calculations and a success criterion of 90% queue precision was selected to minimize false positives. On the test dataset, the F1 measure of the entire pipeline was 72.9%, recall was 60.3%, and queue precision was 90.2%, exceeding success criteria. Conclusions: The experiments demonstrate the feasibility of technology to automate the detection and classification of pulmonary nodule incidental findings in radiology reports. This approach promises to improve healthcare quality by increasing the rate of appropriate lung nodule incidental finding follow-up and treatment without excessive labor or risking overutilization.
{"title":"Automate incidental findings in radiology reports using natural language processing and machine learning to identify and classify lung nodules.","authors":"C. French, D. Kurbegov, D. Spigel, M. Makowski, Samantha R. Terker, P. Clark","doi":"10.1200/jgo.2019.5.suppl.49","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.49","url":null,"abstract":"49 Background: Pulmonary nodule incidental findings challenge providers to balance resource efficiency and high clinical quality. Incidental findings tend to be under evaluated with studies reporting appropriate follow-up rates as low as 29%. The efficient identification of patients with high risk nodules is foundational to ensuring appropriate follow-up and requires the clinical reading and classification of radiology reports. We tested the feasibility of automating this process with natural language processing (NLP) and machine learning (ML). Methods: In cooperation with Sarah Cannon, the Cancer Institute of HCA Healthcare, we conducted a series of experiments on 8,879 free-text, narrative CT radiology reports. A representative sample of health system ED, IP, and OP reports dated from Dec 2015 - April 2017 were divided into a development set for model training and validation, and a test set to evaluate model performance. A “Nodule Model” was trained to detect the reported presence of a pulmonary nodule and a rules-based “Size Model” was developed to extract the size of the nodule in mms. Reports were bucketed into three prediction groups: ≥ 6 mm, <6 mm, and no size indicated. Nodules were placed in a queue for follow-up if the nodule was predicted ≥ 6 mm, or if the nodule had no size indicated and the report contained the word “mass.” The Fleischner Society Guidelines and clinical review informed these definitions. Results: Precision and recall metrics were calculated for multiple model thresholds. A threshold was selected based on the validation set calculations and a success criterion of 90% queue precision was selected to minimize false positives. On the test dataset, the F1 measure of the entire pipeline was 72.9%, recall was 60.3%, and queue precision was 90.2%, exceeding success criteria. Conclusions: The experiments demonstrate the feasibility of technology to automate the detection and classification of pulmonary nodule incidental findings in radiology reports. This approach promises to improve healthcare quality by increasing the rate of appropriate lung nodule incidental finding follow-up and treatment without excessive labor or risking overutilization.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46212648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.113
P. Shilo, A. Kanina
113 Background: Health-Related Quality of Life (HRQoL) is an important issue for elderly patients with colon cancer. We created the expert system which allows to predict low level of HRQoL and accessed it’s quality by using several simulation studies. Methods: We performed a systematic review to figure out the known factors associated with low level of HRQoL in elderly colon cancer patients. The searches were performed in PubMed. We accessed the possible impact of several factors affecting HRQoL, including symptoms, comorbidities and treatment toxicity. All relevant factors were included in prediction model. We assigned the different weights to different factors based on evaluation of clinical studies to develop the logistic regression and Markov stochastic model later. As we needed a binary dependent variable we performed the ROC analysis to figure out an optimal cutoff of HRQoL. Then we simulated a partly virtual dataset based on elderly colon cancer patients diagnosed in Davidovskiy Hospital to evaluate the prediction model quality. All statistical calculations were performed in RStudio. The simulation part was performed using simFrame R package. Results: Twenty two studies with a total number of 2516 patients were included in our systematic review. The 39 factors with different weights were included prediction model with different weights assigned. The weights range varied from 1 to 18.6. The adjusted proportion of summary score's variance (R2 ) varied from 0.09 to 0.47 in univariate analysis. The final logistic regression model quality was moderate: the Nagelkerke R-square coefficient was 57.9. However, the developed model showed a 76% sensitivity and 61% specificity in predicting of lower HRQoL level. Conclusions: Our prediction model allows to prospectively manage of elderly colon cancer patients, making the emphasis on HRQoL. However, the present study has some restrictions: simulation nature of internal validation, possible underestimating of the rare events impact. The long-term comprehensive approach with external validation using large real data analysis is needed to evaluate our prediction model.
{"title":"Development of expert system that improve the decision-making process with an emphasis on health-related quality of life in elderly patients with a colon cancer.","authors":"P. Shilo, A. Kanina","doi":"10.1200/jgo.2019.5.suppl.113","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.113","url":null,"abstract":"113 Background: Health-Related Quality of Life (HRQoL) is an important issue for elderly patients with colon cancer. We created the expert system which allows to predict low level of HRQoL and accessed it’s quality by using several simulation studies. Methods: We performed a systematic review to figure out the known factors associated with low level of HRQoL in elderly colon cancer patients. The searches were performed in PubMed. We accessed the possible impact of several factors affecting HRQoL, including symptoms, comorbidities and treatment toxicity. All relevant factors were included in prediction model. We assigned the different weights to different factors based on evaluation of clinical studies to develop the logistic regression and Markov stochastic model later. As we needed a binary dependent variable we performed the ROC analysis to figure out an optimal cutoff of HRQoL. Then we simulated a partly virtual dataset based on elderly colon cancer patients diagnosed in Davidovskiy Hospital to evaluate the prediction model quality. All statistical calculations were performed in RStudio. The simulation part was performed using simFrame R package. Results: Twenty two studies with a total number of 2516 patients were included in our systematic review. The 39 factors with different weights were included prediction model with different weights assigned. The weights range varied from 1 to 18.6. The adjusted proportion of summary score's variance (R2 ) varied from 0.09 to 0.47 in univariate analysis. The final logistic regression model quality was moderate: the Nagelkerke R-square coefficient was 57.9. However, the developed model showed a 76% sensitivity and 61% specificity in predicting of lower HRQoL level. Conclusions: Our prediction model allows to prospectively manage of elderly colon cancer patients, making the emphasis on HRQoL. However, the present study has some restrictions: simulation nature of internal validation, possible underestimating of the rare events impact. The long-term comprehensive approach with external validation using large real data analysis is needed to evaluate our prediction model.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46724621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.13
Po-Jung Su, Yu-Ann Fang, Yung-Chun Chang, Yung-Chia Kuo, Yung-Chang Lin
13 Background: For de novo metastatic prostate cancer (mPC)) patients, their prognosis may be really different. Some of these patients response very well to hormone therapy with durable survival, but others may be not. For those poor prognosis patients, if we could predict them as high risk patients when diagnosed, and provide aggressive upfront chemotherapy or novel hormonal therapy, they might get better treatment outcomes. Methods: We used data of prostate cancer patients from 2000 to 2016 in Chang Gung Research Database. There are 799 de novo mPC patients with castration. We predicted the possibility for these patients progressed to metastatic castration-resistant prostate cancer (mCRPC) in 1 year and find the high risk group patients. Then we figured out the best features for prediction from the best classifier with Recursive Feature Elimination. Results: The de nove mPC patients who pregressed to mCRPC in 1 year, whose mOS is 21.9 months is worse than who progressed to mCRPC beyond 1 year significantly, whose mOS is 80.7 months. (adjusted hazard ratio[aHR]: 6.43, P<0.001). The overall performance of machine learning by XGBoost is the best in all predictive models for high risk patients. (AUC=0.7000, Accuracy=0.7143). We excluded the features with missing data over 50%, then put all other features in the model. (AUC=0.7042, Accuracy=0.7239). But we got the best performance with only 11 features, including age, time from diagnosis to castration, nadir PSA, hemoglobin, eosinophil/white blood cell ratio, alkaline phosphatase, alanine transaminase, blood urea nitrogen, creatinine, prothrombin time, and secondary primary cancer, by Recursive Feature Elimination. (AUC=0.7131, Accuracy=0.7267). Conclusions: We found the predictive model has better predictive accuracy and shorter manuscript time with less features selected by Recursive Feature Elimination.We can predict high risk group in de novo mPC patients and make better clinical decision for treatment with this XGBoost model.
{"title":"Establish a predictive model for high-risk de novo metastatic prostate cancer patients by machine learning.","authors":"Po-Jung Su, Yu-Ann Fang, Yung-Chun Chang, Yung-Chia Kuo, Yung-Chang Lin","doi":"10.1200/jgo.2019.5.suppl.13","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.13","url":null,"abstract":"13 Background: For de novo metastatic prostate cancer (mPC)) patients, their prognosis may be really different. Some of these patients response very well to hormone therapy with durable survival, but others may be not. For those poor prognosis patients, if we could predict them as high risk patients when diagnosed, and provide aggressive upfront chemotherapy or novel hormonal therapy, they might get better treatment outcomes. Methods: We used data of prostate cancer patients from 2000 to 2016 in Chang Gung Research Database. There are 799 de novo mPC patients with castration. We predicted the possibility for these patients progressed to metastatic castration-resistant prostate cancer (mCRPC) in 1 year and find the high risk group patients. Then we figured out the best features for prediction from the best classifier with Recursive Feature Elimination. Results: The de nove mPC patients who pregressed to mCRPC in 1 year, whose mOS is 21.9 months is worse than who progressed to mCRPC beyond 1 year significantly, whose mOS is 80.7 months. (adjusted hazard ratio[aHR]: 6.43, P<0.001). The overall performance of machine learning by XGBoost is the best in all predictive models for high risk patients. (AUC=0.7000, Accuracy=0.7143). We excluded the features with missing data over 50%, then put all other features in the model. (AUC=0.7042, Accuracy=0.7239). But we got the best performance with only 11 features, including age, time from diagnosis to castration, nadir PSA, hemoglobin, eosinophil/white blood cell ratio, alkaline phosphatase, alanine transaminase, blood urea nitrogen, creatinine, prothrombin time, and secondary primary cancer, by Recursive Feature Elimination. (AUC=0.7131, Accuracy=0.7267). Conclusions: We found the predictive model has better predictive accuracy and shorter manuscript time with less features selected by Recursive Feature Elimination.We can predict high risk group in de novo mPC patients and make better clinical decision for treatment with this XGBoost model.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":"27 24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65926642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.16
W. Cheung, E. Lim, S. Kong
16 Background: Social media channels, such as Twitter, represent relatively new technology platforms for scientific users to disseminate research findings and communicate their views and interpretations to colleagues and followers. To date, the associations between the use of Twitter and the scientific impact of its users are unclear. Methods: All Canadian oncologists who are full members of the American Society of Clinical Oncology were identified from the online membership directory. Users of Twitter were defined as those with an active Twitter account, as of June 2019, and posted at least one tweet within the past year. Data regarding the number of tweets, likes, and followers were collected by an online search of Twitter. Scientific impact of each individual was assessed based on a user’s h-index and number of citations from Google Scholar as well as score from Research Gate. Associations were examined with summary statistics and correlation coefficients. Results: We identified 676 eligible oncologists of whom 80 (12%) and 596 (88%) currently use and do not use Twitter. Among the users, the median number (IQR) of tweets, likes, and followers were 196 (45-865), 325 (86-1,246), and 198 (89-449), respectively. The scientific impact of Twitter users versus non-users was statistically similar (see Table). Likewise, within the group of users, there was no correlation between the number of tweets, likes, and followers and the scientific impact of individuals (correlation coefficients 0.38, 0.34, and 0.41, respectively, all p > 0.05). Conclusions: Only 1 in 10 oncologists use Twitter, but those who use Twitter leveraged this technology platform frequently. There was no association between the use of Twitter and the scientific impact of its users. Views from a minority of oncologists are represented on Twitter. Such bias underscores the need to exercise caution when using social media for scientific knowledge exchange. Regular evaluations of new technologies are warranted to ensure the quality and rigor of their scientific content. [Table: see text]
{"title":"Associations between the use of Twitter as a technology platform in oncology and the scientific impact of its users.","authors":"W. Cheung, E. Lim, S. Kong","doi":"10.1200/jgo.2019.5.suppl.16","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.16","url":null,"abstract":"16 Background: Social media channels, such as Twitter, represent relatively new technology platforms for scientific users to disseminate research findings and communicate their views and interpretations to colleagues and followers. To date, the associations between the use of Twitter and the scientific impact of its users are unclear. Methods: All Canadian oncologists who are full members of the American Society of Clinical Oncology were identified from the online membership directory. Users of Twitter were defined as those with an active Twitter account, as of June 2019, and posted at least one tweet within the past year. Data regarding the number of tweets, likes, and followers were collected by an online search of Twitter. Scientific impact of each individual was assessed based on a user’s h-index and number of citations from Google Scholar as well as score from Research Gate. Associations were examined with summary statistics and correlation coefficients. Results: We identified 676 eligible oncologists of whom 80 (12%) and 596 (88%) currently use and do not use Twitter. Among the users, the median number (IQR) of tweets, likes, and followers were 196 (45-865), 325 (86-1,246), and 198 (89-449), respectively. The scientific impact of Twitter users versus non-users was statistically similar (see Table). Likewise, within the group of users, there was no correlation between the number of tweets, likes, and followers and the scientific impact of individuals (correlation coefficients 0.38, 0.34, and 0.41, respectively, all p > 0.05). Conclusions: Only 1 in 10 oncologists use Twitter, but those who use Twitter leveraged this technology platform frequently. There was no association between the use of Twitter and the scientific impact of its users. Views from a minority of oncologists are represented on Twitter. Such bias underscores the need to exercise caution when using social media for scientific knowledge exchange. Regular evaluations of new technologies are warranted to ensure the quality and rigor of their scientific content. [Table: see text]","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43955973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.89
P. Makondi
89 Background: Liver cancer (LC) is in the seventh most common cancer and the fourth largest cause of cancer deaths. Although significant progress has been made in the prevention and treatment of viral hepatitis; alcoholic liver disease, obesity and diabetes are now emerging as major causes for LC. Recently there has been increase in identification of biomarkers which can predict LC risk and disease progression, but the roles of HOMER3 gene in LC are not known. Methods: First the expression of HOMER3 between normal and tumor tissues was determined using The Cancer Genome Atlas (TCGA), Genetic Expression Omnibus (GEO) and protein atlas datasets. HOMER3 expression at different clinical stage and overall survival (OS) was also determined. The role of HOMER3 on OS in relation to cancer stage, hepatitis virus infection and alcohol intake was also determined. STRING database determined HOMER3 interaction network and TCGA was used to verify the correlation status, and the roles of the network genes on OS. The pathways enriched by HOMER3 were determined by Gene Set Enrichment Analysis (GSEA). Results: HOMER3 was significantly highly expressed in tumor tissues as compared to normal tissues. The expression of HOMER3 correlated positively with clinical stage, with highest expression in advanced stages (Stage 3 and 4), and high HOMER3 expression was associated with poor OS. HOMER3’ s high expression was associated with poor OS in advanced stage, alcohol intake, and in those negative of viral hepatitis infection. HOMER3 interacted with HOMER1, SHANK1, GRM5, GRM1, DLGAP1, SHANK2, DLG4, SHANK3, DLG2 and DLGAP4, with positive correlation to HOMER1, SHANK1, GRM5, GRM1, DLGAP1, DLG4 and DLGAP4 and negative correlation to SHANK2, SHANK3 and DLG2. HOMER1 and DLGAP4 high expression were associated with poor OS while SHANK2, SHANK3 and DLG2 high expression were associated with favorable OS. GRM5 and GRM1 high expression were associated with favorable OS despite being positively correlated with HOMER3. ECM receptor interaction and Notch signaling were the upregulated pathways while Metabolism of xenobiotics by cytochrome p450 and PPAR signaling were the downregulated pathways. Conclusions: HOMER3 may is have a role in liver cancer progression of which its targeting may improve LC outcome.
{"title":"The role of HOMER3 in liver cancer progression.","authors":"P. Makondi","doi":"10.1200/jgo.2019.5.suppl.89","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.89","url":null,"abstract":"89 Background: Liver cancer (LC) is in the seventh most common cancer and the fourth largest cause of cancer deaths. Although significant progress has been made in the prevention and treatment of viral hepatitis; alcoholic liver disease, obesity and diabetes are now emerging as major causes for LC. Recently there has been increase in identification of biomarkers which can predict LC risk and disease progression, but the roles of HOMER3 gene in LC are not known. Methods: First the expression of HOMER3 between normal and tumor tissues was determined using The Cancer Genome Atlas (TCGA), Genetic Expression Omnibus (GEO) and protein atlas datasets. HOMER3 expression at different clinical stage and overall survival (OS) was also determined. The role of HOMER3 on OS in relation to cancer stage, hepatitis virus infection and alcohol intake was also determined. STRING database determined HOMER3 interaction network and TCGA was used to verify the correlation status, and the roles of the network genes on OS. The pathways enriched by HOMER3 were determined by Gene Set Enrichment Analysis (GSEA). Results: HOMER3 was significantly highly expressed in tumor tissues as compared to normal tissues. The expression of HOMER3 correlated positively with clinical stage, with highest expression in advanced stages (Stage 3 and 4), and high HOMER3 expression was associated with poor OS. HOMER3’ s high expression was associated with poor OS in advanced stage, alcohol intake, and in those negative of viral hepatitis infection. HOMER3 interacted with HOMER1, SHANK1, GRM5, GRM1, DLGAP1, SHANK2, DLG4, SHANK3, DLG2 and DLGAP4, with positive correlation to HOMER1, SHANK1, GRM5, GRM1, DLGAP1, DLG4 and DLGAP4 and negative correlation to SHANK2, SHANK3 and DLG2. HOMER1 and DLGAP4 high expression were associated with poor OS while SHANK2, SHANK3 and DLG2 high expression were associated with favorable OS. GRM5 and GRM1 high expression were associated with favorable OS despite being positively correlated with HOMER3. ECM receptor interaction and Notch signaling were the upregulated pathways while Metabolism of xenobiotics by cytochrome p450 and PPAR signaling were the downregulated pathways. Conclusions: HOMER3 may is have a role in liver cancer progression of which its targeting may improve LC outcome.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43979764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.109
Viswanath Gopalakrishnan, S. Sankaran, Mallikarjuna Se, C. Prakash, M. Bakre
109 Background: The utility of multigene prognostic tests in aiding treatment decisions for early stage hormone positive breast cancer patients is well recognized. CanAssist-Breast (CAB) is an immunohistochemistry (IHC) based prognostic test that uses a proprietary algorithm to combine IHC grading of 5 biomarkers and three clinical paramaters (tumor size, node status and Grade) to stratify patients into high or low risk of distant recurrence. CAB has thus far been validated on a retrospective cohort of > 1000 predominantly Asian patients. Distant Metastasis Free Survival (DMFS) of more than 95% was observed with significant separation (P < 0.001) between low-risk and high-risk groups. In this study we demonstrate the usefulness of CanAssist-Breast (CAB) in guiding physicians assess risk of cancer recurrence and to make informed treatment decisions for patients. Methods: A total of 353 Asian patients tested by > 100 physicians were included in this study. Clinical parameters were compiled from hospital data. Treatment decisions were confirmed for > 150 of these patients assess the level of adherence. Risk prediction using the modified Adjuvant! Online protocol was used to compare with performance of CAB. Luminal subtying was performed as per the St. Gallen’s criteria. Results: Majority of patients tested had node negative, T2 and Grade 2 disease. Age and luminal subtypes did not affect the performance of CAB. On comparison with Adjuvant! Online (AOL), CAB categorized twice the number of patients into low-risk. Impact of CAB testing on treatment decisions showed that 96% of low-risk patients were not given chemotherapy and 84% of high-risk patients were given chemotherapy. Overall, we observed that 92% patients were either given or not given chemotherapy based on whether they were stratified as high-risk or low-risk for distant recurrence respectively. Conclusions: CAB stratifies higher percentage of patients into low risk group as compared to AOL. We observed wide acceptance of CAB as a prognostic test for assisting treatment decsions in clinical settings. CAB helped avoid chemotherapy in 70% of patients tested thus providing a cost effective alternative to other prognostic tests currently available.
{"title":"Impact of CanAssist-Breast in clinical treatment decisions in early stage HR+ breast cancer patients: Asian Scenario.","authors":"Viswanath Gopalakrishnan, S. Sankaran, Mallikarjuna Se, C. Prakash, M. Bakre","doi":"10.1200/jgo.2019.5.suppl.109","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.109","url":null,"abstract":"109 Background: The utility of multigene prognostic tests in aiding treatment decisions for early stage hormone positive breast cancer patients is well recognized. CanAssist-Breast (CAB) is an immunohistochemistry (IHC) based prognostic test that uses a proprietary algorithm to combine IHC grading of 5 biomarkers and three clinical paramaters (tumor size, node status and Grade) to stratify patients into high or low risk of distant recurrence. CAB has thus far been validated on a retrospective cohort of > 1000 predominantly Asian patients. Distant Metastasis Free Survival (DMFS) of more than 95% was observed with significant separation (P < 0.001) between low-risk and high-risk groups. In this study we demonstrate the usefulness of CanAssist-Breast (CAB) in guiding physicians assess risk of cancer recurrence and to make informed treatment decisions for patients. Methods: A total of 353 Asian patients tested by > 100 physicians were included in this study. Clinical parameters were compiled from hospital data. Treatment decisions were confirmed for > 150 of these patients assess the level of adherence. Risk prediction using the modified Adjuvant! Online protocol was used to compare with performance of CAB. Luminal subtying was performed as per the St. Gallen’s criteria. Results: Majority of patients tested had node negative, T2 and Grade 2 disease. Age and luminal subtypes did not affect the performance of CAB. On comparison with Adjuvant! Online (AOL), CAB categorized twice the number of patients into low-risk. Impact of CAB testing on treatment decisions showed that 96% of low-risk patients were not given chemotherapy and 84% of high-risk patients were given chemotherapy. Overall, we observed that 92% patients were either given or not given chemotherapy based on whether they were stratified as high-risk or low-risk for distant recurrence respectively. Conclusions: CAB stratifies higher percentage of patients into low risk group as compared to AOL. We observed wide acceptance of CAB as a prognostic test for assisting treatment decsions in clinical settings. CAB helped avoid chemotherapy in 70% of patients tested thus providing a cost effective alternative to other prognostic tests currently available.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42691028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-07DOI: 10.1200/jgo.2019.5.suppl.104
Hyun Chang, H. Hong, Yongho Kim
104 Background: The prognostic value of regulatory T cells (Tregs) in head and neck squamous cell carcinoma (HNSCC) remains unknown. We analyzed the prognostic effect of Tregs in HNSCC with immune activity scores, which reflect the activity status of the seven-step cancer-immunity cycle. Methods: We correlated the 23 immune activity scores and clinicopathologic features of The Cancer Genome Atlas (TCGA) HNSCC using multivariate Cox regression analyses and Kaplan-Meier survival curves. The processed data of immune activity scores were obtained from TIP online tool and the clinicopathologic data were downloaded from TCGA HNSCC database. Results: Immune activity scores of “trafficking of Tregs to tumors” was significantly associated with overall survival (OS) and progression-free survival (PFS). Low activity scores of “trafficking of Tregs to tumors” resulted in shorter OS and PFS. In multivariate analysis, low scores predicted poor OS (adjusted HR = 1.87, 95% CI 1.34-2.60 ; P < 0.001) and were related with unfavorable PFS (adjusted HR = 2.04, 95% CI 1.45-2.86 ; P < 0.001). Conclusions: Immune activity scores of “trafficking of Tregs to tumors” was independent significant prognostic factor in HNSCC. Therefore, assessment of immune activity scores may be useful tools for predicting prognosis in these patients.
{"title":"Prognostic value of trafficking of regulatory T cells to tumors in head and neck cancer patients.","authors":"Hyun Chang, H. Hong, Yongho Kim","doi":"10.1200/jgo.2019.5.suppl.104","DOIUrl":"https://doi.org/10.1200/jgo.2019.5.suppl.104","url":null,"abstract":"104 Background: The prognostic value of regulatory T cells (Tregs) in head and neck squamous cell carcinoma (HNSCC) remains unknown. We analyzed the prognostic effect of Tregs in HNSCC with immune activity scores, which reflect the activity status of the seven-step cancer-immunity cycle. Methods: We correlated the 23 immune activity scores and clinicopathologic features of The Cancer Genome Atlas (TCGA) HNSCC using multivariate Cox regression analyses and Kaplan-Meier survival curves. The processed data of immune activity scores were obtained from TIP online tool and the clinicopathologic data were downloaded from TCGA HNSCC database. Results: Immune activity scores of “trafficking of Tregs to tumors” was significantly associated with overall survival (OS) and progression-free survival (PFS). Low activity scores of “trafficking of Tregs to tumors” resulted in shorter OS and PFS. In multivariate analysis, low scores predicted poor OS (adjusted HR = 1.87, 95% CI 1.34-2.60 ; P < 0.001) and were related with unfavorable PFS (adjusted HR = 2.04, 95% CI 1.45-2.86 ; P < 0.001). Conclusions: Immune activity scores of “trafficking of Tregs to tumors” was independent significant prognostic factor in HNSCC. Therefore, assessment of immune activity scores may be useful tools for predicting prognosis in these patients.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41347466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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