S. Lawal, M. Korenberg, Natalia M. Pittman, M. Mates
{"title":"从化疗前特征预测乳腺癌患者中性粒细胞减少的风险","authors":"S. Lawal, M. Korenberg, Natalia M. Pittman, M. Mates","doi":"10.2174/1875036201408010016","DOIUrl":null,"url":null,"abstract":"A previous study (Pittman, Hopman, Mates) of breast cancer patients undergoing curative chemotherapy (CT) found that the third most common reason for emergency department (ER) visits and hospital admission (HA) was febrile neutropenia. Factors associated with ER visits and HA included (1) stage of the cancer, (2) size of tumor, (3) adjuvant versus neo-adjuvant CT (\"adjuvance\"), and (4) number of CT cycles. We hypothesized that a statistically-significant pre- dictor of neutropenia could be built based on some of these factors, so that risk of neutropenia predicted for a patient feel- ing unwell during CT could be used in weighing need to visit the ER. The number of CT cycles was not used as a factor so that the predictor could calculate the neutropenia risk for a patient before the first CT cycle. Different models were built corresponding to different pre-chemotherapy factors or combinations of factors. The single factor yielding the best classification accuracy was tumor size (Mathews' correlation coefficient � = +0.18, Fisher's exact two-tailed probability P < 0.0374). The odds ratio of developing febrile neutropenia for the predicted high-risk group compared to the predicted low-risk group was 5.1875. Combining tumor size with adjuvance yielded a slightly more accurate predictor (Mathews' correlation coefficient � = +0.19, Fisher's exact two-tailed probability P < 0.0331, odds ratio = 5.5093). Based on the ob- served odds ratios, we conclude that a simple predictor of neutropenia may have value in deciding whether to recommend an ER visit. The predictor is sufficiently fast that it can run conveniently as an Applet on a mobile computing device.","PeriodicalId":38956,"journal":{"name":"Open Bioinformatics Journal","volume":"29 1","pages":"16-21"},"PeriodicalIF":0.0000,"publicationDate":"2015-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Neutropenia Risk in Breast Cancer Patients from Pre- Chemotherapy Characteristics\",\"authors\":\"S. Lawal, M. Korenberg, Natalia M. Pittman, M. Mates\",\"doi\":\"10.2174/1875036201408010016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A previous study (Pittman, Hopman, Mates) of breast cancer patients undergoing curative chemotherapy (CT) found that the third most common reason for emergency department (ER) visits and hospital admission (HA) was febrile neutropenia. Factors associated with ER visits and HA included (1) stage of the cancer, (2) size of tumor, (3) adjuvant versus neo-adjuvant CT (\\\"adjuvance\\\"), and (4) number of CT cycles. We hypothesized that a statistically-significant pre- dictor of neutropenia could be built based on some of these factors, so that risk of neutropenia predicted for a patient feel- ing unwell during CT could be used in weighing need to visit the ER. The number of CT cycles was not used as a factor so that the predictor could calculate the neutropenia risk for a patient before the first CT cycle. Different models were built corresponding to different pre-chemotherapy factors or combinations of factors. The single factor yielding the best classification accuracy was tumor size (Mathews' correlation coefficient � = +0.18, Fisher's exact two-tailed probability P < 0.0374). The odds ratio of developing febrile neutropenia for the predicted high-risk group compared to the predicted low-risk group was 5.1875. Combining tumor size with adjuvance yielded a slightly more accurate predictor (Mathews' correlation coefficient � = +0.19, Fisher's exact two-tailed probability P < 0.0331, odds ratio = 5.5093). Based on the ob- served odds ratios, we conclude that a simple predictor of neutropenia may have value in deciding whether to recommend an ER visit. The predictor is sufficiently fast that it can run conveniently as an Applet on a mobile computing device.\",\"PeriodicalId\":38956,\"journal\":{\"name\":\"Open Bioinformatics Journal\",\"volume\":\"29 1\",\"pages\":\"16-21\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Open Bioinformatics Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1875036201408010016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Bioinformatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1875036201408010016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Predicting Neutropenia Risk in Breast Cancer Patients from Pre- Chemotherapy Characteristics
A previous study (Pittman, Hopman, Mates) of breast cancer patients undergoing curative chemotherapy (CT) found that the third most common reason for emergency department (ER) visits and hospital admission (HA) was febrile neutropenia. Factors associated with ER visits and HA included (1) stage of the cancer, (2) size of tumor, (3) adjuvant versus neo-adjuvant CT ("adjuvance"), and (4) number of CT cycles. We hypothesized that a statistically-significant pre- dictor of neutropenia could be built based on some of these factors, so that risk of neutropenia predicted for a patient feel- ing unwell during CT could be used in weighing need to visit the ER. The number of CT cycles was not used as a factor so that the predictor could calculate the neutropenia risk for a patient before the first CT cycle. Different models were built corresponding to different pre-chemotherapy factors or combinations of factors. The single factor yielding the best classification accuracy was tumor size (Mathews' correlation coefficient � = +0.18, Fisher's exact two-tailed probability P < 0.0374). The odds ratio of developing febrile neutropenia for the predicted high-risk group compared to the predicted low-risk group was 5.1875. Combining tumor size with adjuvance yielded a slightly more accurate predictor (Mathews' correlation coefficient � = +0.19, Fisher's exact two-tailed probability P < 0.0331, odds ratio = 5.5093). Based on the ob- served odds ratios, we conclude that a simple predictor of neutropenia may have value in deciding whether to recommend an ER visit. The predictor is sufficiently fast that it can run conveniently as an Applet on a mobile computing device.
期刊介绍:
The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.