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Rethinking Human Abstraction as the Gold Standard. 反思作为黄金标准的人类抽象。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-25 DOI: 10.1200/CCI-24-00218
Kirk D Wyatt, Brian T Furner, Samuel L Volchenboum

@PedsDataCommons discusses automated approaches for data extraction from electronic health records.

@PedsDataCommons 讨论了从电子健康记录中提取数据的自动化方法。
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引用次数: 0
Waiting to Exhale: The Feasibility and Appropriateness of Home Blood Oxygen Monitoring in Oncology Patients Post-Hospital Discharge. 等待呼气:肿瘤患者出院后进行家庭血氧监测的可行性和适宜性。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-20 DOI: 10.1200/CCI-24-00182
Si-Yang Liu, Sahil D Doshi, AnnMarie Mazzella Ebstein, Jessie Holland, Ayelet Sapir, Micheal Leung, Jennie Huang, Rosanna Fahy, Rori Salvaggio, Aaron Begue, Gilad Kuperman, Fernanda G C Polubriaginof, Peter D Stetson, Jun J Mao, Katherine Panageas, Bob Li, Bobby Daly

Purpose: Pulse oximetry remote patient monitoring (RPM) post-hospital discharge increased during the COVID-19 pandemic as patients and providers sought to limit in-person encounters and provide more care in the home. However, there is limited evidence on the feasibility and appropriateness of pulse oximetry RPM in patients with cancer after hospital discharge.

Methods and materials: This feasibility study enrolled oncology patients discharged after an unexpected admission at the Memorial Sloan Kettering Cancer Center from October 2020 to July 2021. Patients were asked to measure their blood oxygen (O2) level daily during the hours of 9 am-5 pm during a 10-day monitoring period posthospitalization. An automated system alerted clinicians to blood O2 levels below 93.0%. We evaluated the feasibility (>50.0% of patients providing at least one measurement from home) and appropriateness (>50.0% of alerts leading to a clinically meaningful patient interaction) of pulse oximetry RPM.

Results: Sixty-two patients were enrolled in the study, with 53.2% female patients and a median age of 68 years. The most prevalent malignancy was thoracic (62.9%). The feasibility metric was met, with 45 patients (72.6%, 45 of 62) providing blood O2 levels at least once during the 10-day monitoring program. The appropriateness threshold was not met; of the 121 alerts, only 39.7% (48 alerts) was linked to a clinically meaningful interaction.

Conclusion: This feasibility study showed that while patients with cancer were willing to measure blood O2 levels at home, most alerts did not result in meaningful clinical interactions. There is a need for improved patient support systems and logistical infrastructure to support appropriate use of RPM at home.

目的:在 COVID-19 大流行期间,出院后脉搏血氧仪远程患者监护 (RPM) 有所增加,因为患者和医疗服务提供者都在努力限制面对面的接触,并在家中提供更多的护理服务。然而,有关癌症患者出院后使用脉搏血氧仪进行远程患者监护的可行性和适宜性的证据却很有限:这项可行性研究招募了 2020 年 10 月至 2021 年 7 月期间在纪念斯隆-凯特琳癌症中心意外入院后出院的肿瘤患者。要求患者在出院后的 10 天监测期内,每天上午 9 点至下午 5 点测量血氧 (O2) 水平。当血氧水平低于 93.0% 时,自动系统会向临床医生发出警报。我们评估了脉搏血氧仪 RPM 的可行性(>50.0% 的患者至少在家中进行了一次测量)和适当性(>50.0% 的警报导致了有临床意义的患者互动):研究共招募了 62 名患者,其中女性患者占 53.2%,中位年龄为 68 岁。最常见的恶性肿瘤是胸部肿瘤(62.9%)。有 45 名患者(62 人中有 45 人,占 72.6%)在为期 10 天的监测计划中至少提供了一次血氧水平,达到了可行性指标。未达到适当性阈值;在 121 次警报中,只有 39.7% (48 次警报)与有临床意义的互动相关联:这项可行性研究表明,虽然癌症患者愿意在家中测量血氧水平,但大多数警报并未产生有意义的临床互动。有必要改进患者支持系统和后勤基础设施,以支持在家中适当使用 RPM。
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引用次数: 0
Automated Electronic Health Record Data Extraction and Curation Using ExtractEHR. 使用 ExtractEHR 自动提取和整理电子健康记录数据。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-25 DOI: 10.1200/CCI.24.00100
Tamara P Miller, Kelly D Getz, Edward Krause, Yun Gun Jo, Sandhya Charapala, M Monica Gramatages, Karen Rabin, Michael E Scheurer, Jennifer J Wilkes, Brian T Fisher, Richard Aplenc

Purpose: Although the potential transformative effect of electronic health record (EHR) data on clinical research in adult patient populations has been very extensively discussed, the effect on pediatric oncology research has been limited. Multiple factors contribute to this more limited effect, including the paucity of pediatric cancer cases in commercial EHR-derived cancer data sets and phenotypic case identification challenges in pediatric federated EHR data.

Methods: The ExtractEHR software package was initially developed as a tool to improve clinical trial adverse event reporting but has expanded its use cases to include the development of multisite EHR data sets and the support of cancer cohorts. ExtractEHR enables customized, automated data extraction from the EHR that, when implemented across multiple hospitals, can create pediatric cancer EHR data sets to address a very wide range of research questions in pediatric oncology. After ExtractEHR data acquisition, EHR data can be cleaned and graded using CleanEHR and GradeEHR, companion software packages.

Results: ExtractEHR has been installed at four leading pediatric institutions: Children's Healthcare of Atlanta, Children's Hospital of Philadelphia, Texas Children's Hospital, and Seattle Children's Hospital.

Conclusion: ExtractEHR has supported multiple use cases, including five clinical epidemiology studies, multicenter clinical trials, and cancer cohort assembly. Work is ongoing to develop Fast Health care Interoperability Resources ExtractEHR and implement other sustainability and scalability enhancements.

目的:虽然电子健康记录(EHR)数据对成人患者群体临床研究的潜在变革性影响已被广泛讨论,但对儿科肿瘤研究的影响却很有限。造成这种有限影响的因素有多种,包括商业电子病历衍生的癌症数据集中儿科癌症病例极少,以及儿科联合电子病历数据中的表型病例识别难题:方法:ExtractEHR 软件包最初是作为改进临床试验不良事件报告的工具而开发的,但其用途已扩展到包括开发多站点 EHR 数据集和支持癌症队列。ExtractEHR 可从电子病历中自动提取定制数据,在多家医院使用后,可创建儿科癌症电子病历数据集,以解决儿科肿瘤学中的各种研究问题。ExtractEHR 数据采集完成后,可使用配套软件 CleanEHR 和 GradeEHR 对电子病历数据进行清理和分级:结果:ExtractEHR 已在四家领先的儿科机构安装:结果:亚特兰大儿童医疗保健中心、费城儿童医院、德克萨斯儿童医院和西雅图儿童医院已安装了 ExtractEHR:结论:ExtractEHR 支持多种使用案例,包括五项临床流行病学研究、多中心临床试验和癌症队列组装。目前正在开发快速医疗互操作性资源 ExtractEHR,并实施其他可持续性和可扩展性增强措施。
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引用次数: 0
Usage of the National Cancer Institute Cancer Research Data Commons by Researchers: A Scoping Review of the Literature. 研究人员对美国国家癌症研究所癌症研究公共数据的使用:文献综述》。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-13 DOI: 10.1200/CCI.24.00116
Zhaoyi Chen, Erika Kim, Tanja Davidsen, Jill S Barnholtz-Sloan

Purpose: Over the past decade, significant surges in cancer data of all types have happened. To promote sharing and use of these rich data, the National Cancer Institute's Cancer Research Data Commons (CRDC) was developed as a cloud-based infrastructure that provides a large, comprehensive, and expanding collection of cancer data with tools for analysis. We conducted this scoping review of articles to provide an overview of how CRDC resources are being used by cancer researchers.

Methods: A thorough literature search was conducted to identify all relevant publications. We included publications that directly cited CRDC resources to specifically examine the impact and contributions of CRDC by itself. We summarized the distributions and trends of how CRDC components were used by the research community and discussed current research gaps and future opportunities.

Results: In terms of CRDC resources used by the research community, encouraging trends in utilization were observed, suggesting that CRDC has become an important building block for fostering a wide range of cancer research. We also noted a few areas where current applications are rather lacking and provided insights on how improvements can be made by CRDC and research community.

Conclusion: CRDC, as the foundation of a National Cancer Data Ecosystem, will continue empowering the research community to effectively leverage cancer-related data, uncover novel strategies, and address the needs of patients with cancer, ultimately combatting this disease more effectively.

目的:过去十年间,各类癌症数据激增。为了促进这些丰富数据的共享和使用,美国国立癌症研究所(National Cancer Institute)开发了癌症研究数据公共平台(Cancer Research Data Commons,CRDC),作为一个基于云的基础设施,它提供了大量全面且不断扩展的癌症数据,并附带分析工具。我们对相关文章进行了综述,以概述癌症研究人员如何使用 CRDC 资源:我们进行了全面的文献检索,以确定所有相关出版物。我们纳入了直接引用 CRDC 资源的出版物,以具体研究 CRDC 本身的影响和贡献。我们总结了研究界如何使用 CRDC 组件的分布情况和趋势,并讨论了当前的研究差距和未来的机会:就研究界使用 CRDC 资源的情况而言,我们观察到了令人鼓舞的使用趋势,这表明 CRDC 已成为促进广泛癌症研究的重要基石。我们还注意到当前应用相当缺乏的几个领域,并就 CRDC 和研究界如何改进提供了见解:作为国家癌症数据生态系统的基础,CRDC 将继续增强研究界的能力,以有效利用癌症相关数据、发现新策略并满足癌症患者的需求,最终更有效地防治这一疾病。
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引用次数: 0
Remote Patient Monitoring Using Mobile Health Technology in Cancer Care and Research: Patients' Views and Preferences. 在癌症护理和研究中使用移动医疗技术对患者进行远程监控:患者的观点和偏好。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-12 DOI: 10.1200/CCI.24.00092
Dominique G Stuijt, Eva E M van Doeveren, Milan Kos, Marijn Eversdijk, Jacobus J Bosch, Adriaan D Bins, Marieke A R Bak, Martijn G H van Oijen

Purpose: There is an increasing interest in studying the potential of mobile health (mHealth) technologies, such as smartphone apps and wearables, as monitoring tools for patients with cancer during or after their treatment. However, little research is dedicated to exploring the opinions and concerns of patients regarding the adoption of these technologies. This study aimed to gain insight into patients' perspectives and preferences for participating in mHealth-based monitoring in cancer care.

Methods: A qualitative study comprising semistructured interviews was conducted in the Netherlands between April and June 2023. Participants were eligible if they were 18 years or older with a current or past diagnosis of cancer. The interview guide was developed on the basis of the technology acceptance model, with main themes being use, communication, trust, privacy, and expectations.

Results: Thirteen participants with urologic primary cancer were interviewed. Most patients had already some familiarity with the use of digital monitoring devices or wearables. Main barriers included persistent reminders of the illness, receiving notifications deemed unnecessary or unwanted, and the acknowledgment that mHealth technology does not serve as a substitute for human doctors. Conversely, patients recognized the potential for time-savings through the utilization of mHealth, viewed active monitoring as nonburdensome, considered mHealth a tool for reducing the communication threshold with their doctor, and expressed willingness to adopt such a platform if they perceived personal or societal relevance.

Conclusion: This study has elucidated which factors are important for successful development of mHealth for patients with cancer. While both barriers and facilitators play a role, patients' attitudes were positive toward the implementation of remote digital monitoring, showing promising prospects for future research of mHealth in oncology.

目的:人们对研究移动医疗(mHealth)技术(如智能手机应用程序和可穿戴设备)作为癌症患者治疗期间或治疗后的监测工具的潜力越来越感兴趣。然而,很少有研究专门探讨患者对采用这些技术的意见和担忧。本研究旨在深入了解患者对参与基于移动医疗的癌症护理监测的看法和偏好:2023 年 4 月至 6 月期间,在荷兰进行了一项定性研究,包括半结构式访谈。年满 18 周岁且目前或过去曾被诊断患有癌症的患者均有资格参与。访谈指南是在技术接受模型的基础上制定的,主要主题包括使用、沟通、信任、隐私和期望:13 名泌尿系统原发性癌症患者接受了访谈。大多数患者对数字监测设备或可穿戴设备的使用已有一定了解。主要障碍包括持续提醒病情、接收不必要或不想要的通知,以及认识到移动医疗技术不能替代人类医生。相反,患者认识到了利用移动医疗节省时间的潜力,认为主动监测不会造成负担,认为移动医疗是降低与医生沟通门槛的工具,并表示如果他们认为与个人或社会相关,他们愿意采用这样的平台:本研究阐明了哪些因素对癌症患者移动医疗的成功发展至关重要。虽然障碍和促进因素都起着作用,但患者对实施远程数字监测的态度是积极的,这为移动医疗在肿瘤学领域的未来研究展示了广阔的前景。
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引用次数: 0
Identification of Individuals With Hereditary Cancer Risk Through Multiple Data Sources: A Population-Based Method Using the GARDE Platform and The Utah Population Database. 通过多种数据源识别具有遗传性癌症风险的个体:使用 GARDE 平台和犹他州人口数据库的人口方法。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-11-01 Epub Date: 2024-11-21 DOI: 10.1200/CCI-24-00142
Guilherme Del Fiol, Michael J Madsen, Richard L Bradshaw, Michael G Newman, Kimberly A Kaphingst, Sean V Tavtigian, Nicola J Camp

Purpose: The GARDE platform uses family history reported in the electronic health record (EHR) to systematically identify eligible patients for genetic testing for hereditary cancer syndromes. The goal of this study was to evaluate the change in effectiveness of GARDE to identify eligible individuals when more comprehensive family history data are provided, thus quantifying the impact of underdocumentation.

Methods: A cohort of 133,764 patients at the University of Utah Health was analyzed with GARDE comparing identification rates using EHR data versus EHR plus data from a statewide population database, the Utah Population Database (UPDB).

Results: Compared with EHR alone, EHR + UPDB increased the rate of individuals eligible for genetic testing from 4.1% to 9.2%. In the 44,692 individuals with the most comprehensive family history, eligibility more than quadrupled from 4.6% (EHR alone) to 19.3% (EHR + UPDB). The increase was significant across all demographics, but disparities still remained for historically marginalized minorities (9.2%-13.9% in non-White races compared with 19.7% in White races).

Conclusion: Augmenting EHR data with family history data from the UPDB substantially improved the detection of individuals eligible for genetic testing of hereditary cancer syndromes in all subgroups. This underscores the importance of improving methods for acquiring family history, in person or in silico. However, these increases did not ameliorate disparities. Continuous disparities are unlikely to be explained by incomplete family history alone and may also be because susceptibility genes, risk variants, and screening guidelines were discovered and developed largely in White races. Addressing disparities will require intentional data collection of family history in historically marginalized minorities and the promotion of genetic and risk assessment studies in more diverse populations to ensure equity and health care.

目的:GARDE 平台利用电子病历 (EHR) 中报告的家族史系统地识别符合遗传性癌症综合征基因检测条件的患者。本研究的目的是评估当提供更全面的家族史数据时,GARDE 识别合格个体的有效性的变化,从而量化记录不足的影响:方法: 使用 GARDE 分析了犹他大学健康中心的 133764 名患者队列,比较了使用电子病历数据和电子病历加上来自全州人口数据库(犹他人口数据库,UPDB)的数据的识别率:结果:与仅使用电子病历相比,电子病历+UPDB 使符合基因检测条件的患者比例从 4.1% 提高到 9.2%。在具有最全面家族史的 44,692 人中,符合基因检测条件的人数增加了四倍多,从 4.6%(仅 EHR)增至 19.3%(EHR + UPDB)。在所有人口统计数据中,这一比例都有显著提高,但历史上被边缘化的少数族裔仍存在差距(非白人种族为 9.2%-13.9%,而白人种族为 19.7%):结论:用UPDB的家族史数据增强电子病历数据大大提高了对所有亚群中符合遗传性癌症综合征基因检测条件的个体的检测率。这凸显了改进获取家族史方法的重要性,无论是亲自获取还是在硅学中获取。然而,这些增加并没有改善差异。持续的差异不太可能仅由不完整的家族史来解释,也可能是因为易感基因、风险变异和筛查指南主要是在白人种族中发现和制定的。要解决差异问题,就需要有意识地收集历史上被边缘化的少数民族的家族史数据,并在更多不同的人群中推广遗传和风险评估研究,以确保公平和医疗保健。
{"title":"Identification of Individuals With Hereditary Cancer Risk Through Multiple Data Sources: A Population-Based Method Using the GARDE Platform and The Utah Population Database.","authors":"Guilherme Del Fiol, Michael J Madsen, Richard L Bradshaw, Michael G Newman, Kimberly A Kaphingst, Sean V Tavtigian, Nicola J Camp","doi":"10.1200/CCI-24-00142","DOIUrl":"10.1200/CCI-24-00142","url":null,"abstract":"<p><strong>Purpose: </strong>The GARDE platform uses family history reported in the electronic health record (EHR) to systematically identify eligible patients for genetic testing for hereditary cancer syndromes. The goal of this study was to evaluate the change in effectiveness of GARDE to identify eligible individuals when more comprehensive family history data are provided, thus quantifying the impact of underdocumentation.</p><p><strong>Methods: </strong>A cohort of 133,764 patients at the University of Utah Health was analyzed with GARDE comparing identification rates using EHR data versus EHR plus data from a statewide population database, the Utah Population Database (UPDB).</p><p><strong>Results: </strong>Compared with EHR alone, EHR + UPDB increased the rate of individuals eligible for genetic testing from 4.1% to 9.2%. In the 44,692 individuals with the most comprehensive family history, eligibility more than quadrupled from 4.6% (EHR alone) to 19.3% (EHR + UPDB). The increase was significant across all demographics, but disparities still remained for historically marginalized minorities (9.2%-13.9% in non-White races compared with 19.7% in White races).</p><p><strong>Conclusion: </strong>Augmenting EHR data with family history data from the UPDB substantially improved the detection of individuals eligible for genetic testing of hereditary cancer syndromes in all subgroups. This underscores the importance of improving methods for acquiring family history, in person or in silico. However, these increases did not ameliorate disparities. Continuous disparities are unlikely to be explained by incomplete family history alone and may also be because susceptibility genes, risk variants, and screening guidelines were discovered and developed largely in White races. Addressing disparities will require intentional data collection of family history in historically marginalized minorities and the promotion of genetic and risk assessment studies in more diverse populations to ensure equity and health care.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"8 ","pages":"e2400142"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11583850/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Can Digital Health Improve Therapeutic Compliance in Oncology? 数字医疗能提高肿瘤治疗的依从性吗?
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-10-01 Epub Date: 2024-10-25 DOI: 10.1200/CCI-24-00205
Pierre Etienne Heudel, Myriam Ait Ichou, Bertrand Favier, Hugo Crochet, Jean-Yves Blay

Purpose: Therapeutic compliance, or adherence, is critical in oncology because of the complexity and duration of cancer treatment regimens. Nonadherence can lead to suboptimal therapeutic outcomes, increased disease progression, higher mortality rates, and elevated health care costs. Traditional methods to enhance compliance, such as patient education and regular follow-ups, have shown limited success.

Materials and methods: This review examines the potential of digital health technologies to improve adherence in oncology. Various studies and trials are analyzed to assess the effectiveness of these technologies in supporting patients with cancer.

Results: mHealth applications have been shown to improve medication adherence through features like medication reminders and symptom tracking. Telemedicine facilitates continuous care and reduces the need for travel, significantly improving adherence and patient satisfaction. Patient-reported outcome measures enhance clinical decision making and personalized treatment plans by incorporating patient feedback. Electronic medical records and patient portals improve compliance by providing easy access to medical information and fostering better patient-provider communication. Connected pillboxes aid in consistent medication intake and reduce dispensing errors.

Conclusion: Digital health technologies offer significant benefits in oncology by enhancing patient engagement, improving adherence to treatment protocols, and enabling comprehensive cancer care management. However, challenges such as the digital divide, data privacy concerns, and the need for tailored interventions must be addressed. Future research should focus on evaluating the effectiveness of digital interventions and developing personalized digital health tools to maximize therapeutic compliance.

目的:由于癌症治疗方案的复杂性和持续时间,治疗依从性(或称依从性)在肿瘤学中至关重要。不坚持治疗会导致治疗效果不理想、疾病进展加剧、死亡率升高以及医疗费用增加。提高依从性的传统方法,如患者教育和定期随访,成效有限:本综述探讨了数字医疗技术在提高肿瘤治疗依从性方面的潜力。结果表明:移动医疗应用通过用药提醒和症状跟踪等功能提高了患者的用药依从性。远程医疗为持续护理提供了便利,减少了出差的需要,大大提高了患者的依从性和满意度。病人报告的结果测量通过纳入病人的反馈意见,加强了临床决策和个性化治疗计划。电子病历和患者门户网站通过提供便捷的医疗信息获取途径和促进患者与医护人员之间更好的沟通,提高了患者的依从性。联网药盒有助于保持药物摄入的一致性并减少配药错误:数字医疗技术通过提高患者参与度、改善治疗方案的依从性以及实现全面的癌症护理管理,为肿瘤学带来了巨大的益处。然而,数字鸿沟、数据隐私问题以及定制干预措施的必要性等挑战必须得到解决。未来的研究应侧重于评估数字干预措施的有效性和开发个性化数字健康工具,以最大限度地提高治疗依从性。
{"title":"Can Digital Health Improve Therapeutic Compliance in Oncology?","authors":"Pierre Etienne Heudel, Myriam Ait Ichou, Bertrand Favier, Hugo Crochet, Jean-Yves Blay","doi":"10.1200/CCI-24-00205","DOIUrl":"https://doi.org/10.1200/CCI-24-00205","url":null,"abstract":"<p><strong>Purpose: </strong>Therapeutic compliance, or adherence, is critical in oncology because of the complexity and duration of cancer treatment regimens. Nonadherence can lead to suboptimal therapeutic outcomes, increased disease progression, higher mortality rates, and elevated health care costs. Traditional methods to enhance compliance, such as patient education and regular follow-ups, have shown limited success.</p><p><strong>Materials and methods: </strong>This review examines the potential of digital health technologies to improve adherence in oncology. Various studies and trials are analyzed to assess the effectiveness of these technologies in supporting patients with cancer.</p><p><strong>Results: </strong>mHealth applications have been shown to improve medication adherence through features like medication reminders and symptom tracking. Telemedicine facilitates continuous care and reduces the need for travel, significantly improving adherence and patient satisfaction. Patient-reported outcome measures enhance clinical decision making and personalized treatment plans by incorporating patient feedback. Electronic medical records and patient portals improve compliance by providing easy access to medical information and fostering better patient-provider communication. Connected pillboxes aid in consistent medication intake and reduce dispensing errors.</p><p><strong>Conclusion: </strong>Digital health technologies offer significant benefits in oncology by enhancing patient engagement, improving adherence to treatment protocols, and enabling comprehensive cancer care management. However, challenges such as the digital divide, data privacy concerns, and the need for tailored interventions must be addressed. Future research should focus on evaluating the effectiveness of digital interventions and developing personalized digital health tools to maximize therapeutic compliance.</p>","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"8 ","pages":"e2400205"},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512715","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}
引用次数: 0
Informatics and Artificial Intelligence-Guided Assessment of the Regulatory and Translational Research Landscape of First-in-Class Oncology Drugs in the United States, 2018-2022. 2018-2022年信息学和人工智能指导下的美国一流肿瘤药物监管和转化研究前景评估》(Informatics and Artificial Intelligence-Guided Assessment of the Regulatory and Translational Research Landscape of First-in-Class Oncology Drugs in the United States, 2018-2022)。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-10-01 DOI: 10.1200/CCI.24.00087
Jay G Ronquillo, Brett South, Prakash Naik, Rominder Singh, Magdia De Jesus, Stephen J Watt, Aida Habtezion

Purpose: Cancer drug development remains a critical but challenging process that affects millions of patients and their families. Using biomedical informatics and artificial intelligence (AI) approaches, we assessed the regulatory and translational research landscape defining successful first-in-class drugs for patients with cancer.

Methods: This is a retrospective observational study of all novel first-in-class drugs approved by the US Food and Drug Administration (FDA) from 2018 to 2022, stratified by cancer versus noncancer drugs. A biomedical informatics pipeline leveraging interoperability standards and ChatGPT performed integration and analysis of public databases provided by the FDA, National Institutes of Health, and WHO.

Results: Between 2018 and 2022, the FDA approved a total of 247 novel drugs, of which 107 (43.3%) were first-in-class drugs involving a new biologic target. Of these first-in-class drugs, 30 (28%) treatments were indicated for patients with cancer, including 19 (63.3%) for solid tumors and the remaining 11 (36.7%) for hematologic cancers. A median of 68 publications of basic, clinical, and other relevant translational science preceded successful FDA approval of first-in-class cancer drugs, with oncology-related treatments involving fewer median years of target-based research than therapies not related to cancer (33 v 43 years; P < .05). Overall, 94.4% of first-in-class drugs had at least 25 years of target-related research papers, while 85.5% of first-in-class drugs had at least 10 years of translational research publications.

Conclusion: Novel first-in-class cancer treatments are defined by diverse clinical indications, personalized molecular targets, dependence on expedited regulatory pathways, and translational research metrics reflecting this complex landscape. Biomedical informatics and AI provide scalable, data-driven ways to assess and even address important challenges in the drug development pipeline.

目的:癌症药物开发仍然是一个关键但极具挑战性的过程,影响着数百万患者及其家庭。利用生物医学信息学和人工智能(AI)方法,我们评估了为癌症患者成功定义首创药物的监管和转化研究情况:这是一项回顾性观察研究,研究对象是美国食品和药物管理局(FDA)从 2018 年到 2022 年批准的所有新型首创药物,并按癌症药物与非癌症药物进行了分层。生物医学信息学管道利用互操作性标准和 ChatGPT 对 FDA、美国国立卫生研究院和世卫组织提供的公共数据库进行了整合和分析:2018 年至 2022 年间,FDA 共批准了 247 种新型药物,其中 107 种(43.3%)是涉及新生物靶点的首创药物。在这些首创药物中,有30种(28%)治疗方法适用于癌症患者,其中19种(63.3%)适用于实体瘤,其余11种(36.7%)适用于血液肿瘤。在FDA成功批准一类抗癌药物之前,基础、临床和其他相关转化科学的中位数论文发表量为68篇,与癌症无关的疗法相比,肿瘤相关疗法的靶向研究中位数年数较少(33年v 43年;P < .05)。总体而言,94.4%的一类新药至少发表了25年的靶点相关研究论文,而85.5%的一类新药至少发表了10年的转化研究论文:结论:新的一流癌症治疗方法由多样化的临床适应症、个性化的分子靶点、对快速监管途径的依赖以及反映这一复杂情况的转化研究指标所定义。生物医学信息学和人工智能提供了可扩展、数据驱动的方法来评估甚至解决药物开发管道中的重要挑战。
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引用次数: 0
Drug's Journey of a Thousand Papers Begins With a Single Step. 药物的千纸之旅始于足下。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-10-01 Epub Date: 2024-10-14 DOI: 10.1200/CCI-24-00225
Pasquale F Innominato, Nicholas I Wreglesworth, Alessio Antonini, Zachary S Buchwald
{"title":"Drug's Journey of a Thousand Papers Begins With a Single Step.","authors":"Pasquale F Innominato, Nicholas I Wreglesworth, Alessio Antonini, Zachary S Buchwald","doi":"10.1200/CCI-24-00225","DOIUrl":"https://doi.org/10.1200/CCI-24-00225","url":null,"abstract":"","PeriodicalId":51626,"journal":{"name":"JCO Clinical Cancer Informatics","volume":"8 ","pages":"e2400225"},"PeriodicalIF":3.3,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480457","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}
引用次数: 0
Development and Portability of a Text Mining Algorithm for Capturing Disease Progression in Electronic Health Records of Patients With Stage IV Non-Small Cell Lung Cancer. 在 IV 期非小细胞肺癌患者电子健康记录中捕捉疾病进展的文本挖掘算法的开发与可移植性。
IF 3.3 Q2 ONCOLOGY Pub Date : 2024-10-01 Epub Date: 2024-10-04 DOI: 10.1200/CCI.24.00053
M V Verschueren, H Abedian Kalkhoran, M Deenen, B E E M van den Borne, J Zwaveling, L E Visser, L T Bloem, B J M Peters, E M W van de Garde

Purpose: The objective was to develop and evaluate the portability of a text mining algorithm for prospectively capturing disease progression in electronic health record (EHR) data of patients with metastatic non-small cell lung cancer (mNSCLC) treated with immunochemotherapy.

Methods: This study used EHR data from patients with mNSCLC receiving immunochemotherapy (between October 1, 2018, and December 31, 2022) in four Dutch hospitals. A text mining algorithm for capturing disease progression was developed in hospitals 1 and 2 and then transferred to hospitals 3 and 4 to evaluate portability. Performance metrics were calculated by comparing its outcomes with manual chart review. In addition, data were simulated to come available over time to assess performance in real-time applications. Median progression-free survival (PFS) was calculated using the Kaplan-Meier method to compare text mining with manual chart review.

Results: During development and portability, the text mining algorithm performed well in capturing disease progression, with all performance scores >90%. When real-time performance was simulated, the performance scores in all four hospitals exceeded 90% from week 15 after the start of follow-up. Although the exact progression dates varied in 46 patients of 157 patients with progressive disease, the number of patients labeled with progression too early (n = 24) and too late (n = 22) was well balanced with discrepancies ranging from -116 to 384 days. Nevertheless, the PFS curves constructed with text mining and manual chart review were highly similar for each hospital.

Conclusion: In this study, an accurate text mining algorithm for capturing disease progression in the EHR data of patients with mNSCLC was developed. The algorithm was portable across different hospitals, and the performance over time was good, making this an interesting approach for prospective follow-up of multicenter cohorts.

目的:本研究旨在开发和评估一种文本挖掘算法的可移植性,以前瞻性地捕捉接受免疫化疗的转移性非小细胞肺癌(mNSCLC)患者电子健康记录(EHR)数据中的疾病进展情况:本研究使用了四家荷兰医院接受免疫化疗的mNSCLC患者的电子病历数据(2018年10月1日至2022年12月31日期间)。在1号和2号医院开发了一种用于捕捉疾病进展的文本挖掘算法,然后将其转移到3号和4号医院,以评估其可移植性。通过将其结果与人工病历审查进行比较,计算出性能指标。此外,还模拟了数据随时间推移的可用性,以评估实时应用的性能。使用 Kaplan-Meier 法计算无进展生存期(PFS)中位数,以比较文本挖掘与人工病历审查的结果:结果:在开发和移植过程中,文本挖掘算法在捕捉疾病进展方面表现良好,所有性能得分均大于 90%。在模拟实时性能时,从随访开始后的第 15 周起,所有四家医院的性能得分都超过了 90%。虽然在 157 例疾病进展患者中,有 46 例患者的确切进展日期不尽相同,但标记为进展过早(24 例)和过晚(22 例)的患者数量非常均衡,差异范围从-116 天到 384 天不等。尽管如此,每家医院通过文本挖掘和人工病历审查构建的 PFS 曲线高度相似:本研究开发了一种准确的文本挖掘算法,用于捕捉 mNSCLC 患者电子病历数据中的疾病进展情况。该算法可在不同医院间移植,且随时间推移性能良好,因此是一种用于多中心队列前瞻性随访的有趣方法。
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引用次数: 0
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JCO Clinical Cancer Informatics
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