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PURPOSEThe burden of cancer disproportionately affects low- and middle-income countries. Low 5-year survival figures for children with cancer in low-income countries are due to late presentation at diagnosis, treatment abandonment, absence of sophisticated multidisciplinary care, and lack of adequate resources. The reasons for late presentation are partly due to limited awareness of cancer symptoms, high treatment costs, and facility-level barriers to timely access to treatment. Given the systemic challenges, the regional need for palliative oncology care for children care is high. Despite the enormity of the need for palliative oncology for children with cancer in Africa, its level of development remains poor. This paper presents the evidence on the status of palliative oncology care for children in sub-Saharan Africa.METHODSThis review provides an overview of the current status of palliative oncology care for children in sub-Saharan Africa, using the WHO building blocks for health systems strengthening as reference points, before proposing a forward-looking prioritized agenda for its development.RESULTSWe noted that survival rates for children with cancer remain much poorer in Africa compared with developed countries and palliative oncology care resources are scant. Our results also show low coverage for palliative oncology care services for children, lack of a critical mass of health workers with the skills to deliver the care, a lack of robust documentation of the burden of cancer, widespread lack of access to essential controlled medicines, limited funding from government and limited coverage for palliative oncology care in most cancer control plans.CONCLUSIONThis review highlights priority areas for action that align to the WHO health system building blocks for strengthening health systems.

Recognizing the increase in cancer incidence globally and the need for effective cancer control interventions, several organizations, professional bodies, and international institutions have proposed strategies to improve treatment options and reduce mortality along with minimizing overall incidence. Despite these efforts, an estimated 9.6 million deaths in 2018 was attributed to this noncommunicable disease, making it the second leading cause of death worldwide. Left unchecked, this will further increase in scale, with an estimated 29.5 million new cases and 16.3 million deaths occurring worldwide in 2040. Although it is known and generally accepted that cancer services must include radiotherapy, such access is still very limited in many parts of the world, especially in low- and middle-income countries. After thorough review of the current status of radiotherapy including programs worldwide, as well as achievements and challenges at the global level, the International Atomic Energy Agency convened an international group of experts representing various radiation oncology societies to take a closer look into the current status of radiotherapy and provide a road map for future directions in this field. It was concluded that the plethora of global and regional initiatives would benefit further from the existence of a central framework, including an easily accessible repository through which better coordination can be done. Supporting this framework, a practical inventory of competencies needs to be made available on a global level emphasizing the knowledge, skills, and behavior required for a safe, sustainable, and professional practice for various settings. This white paper presents the current status of global radiotherapy and future directions for the community. It forms the basis for an action plan to be developed with professional societies worldwide.

A paper analytic device, the chemoPAD, was developed and validated to visually detect methotrexate, doxorubicin, cisplatin, and oxaliplatin at concentrations commonly found in injectable dosage forms. By testing residual solution after patient treatment, the chemoPAD can be used to monitor drug quality without restriction of patient access to medication. The chemoPAD is produced by wax printing on Ahlstrom paper to create separate reaction areas and deposits small amounts of chemicals to create color changes in response to different active pharmaceutical ingredients (APIs). This creates a unique color bar code to identify each medication. Internal validation studies show that the chemoPAD has excellent sensitivity and specificity to differentiate between samples of 100% and 0% API, which is the distinction relevant to the majority of reported falsified chemotherapy cases. The platinum-containing drugs, cisplatin and oxaliplatin, can be detected semiquantitatively. The cards can be read either visually by comparison with a standard image or by using computer image analysis. Dosage forms were collected from the Ethiopian health care system and analyzed with the chemoPAD followed by high-performance liquid chromatography. A substandard sample was discovered and reported to the Ethiopian Food Medicine and Healthcare Administration and Control Authority.

Purpose: Consent processes are critical for clinical care and research and may benefit from incorporating digital strategies. We compared an electronic informed consent (eIC) option to paper consent across four outcomes: (1) technology burden, (2) protocol comprehension, (3) participant agency (ability to self-advocate), and (4) completion of required document fields., Methods: We assessed participant experience with eIC processes compared with traditional paper-based consenting using surveys and compared completeness of required fields, over 3 years (2019-2021). Participants who consented to a clinical trial at a large academic cancer center via paper or eIC were invited to either pre-COVID-19 pandemic survey 1 (technology burden) or intrapandemic survey 2 (comprehension and agency). Consent document completeness was assessed via electronic health records., Results: On survey 1, 83% of participants (n = 777) indicated eIC was easy or very easy to use; discomfort with technology overall was not correlated with discomfort using eIC. For survey 2, eIC (n = 262) and paper consenters (n = 193) had similar comprehension scores. All participants responded favorably to at least five of six agency statements; however, eIC generated a higher proportion of positive free-text comments ( P < .05), with themes such as thoroughness of the discussion and consenter professionalism. eIC use yielded no completeness errors across 235 consents versus 6.4% for paper ( P < .001)., Conclusion: Our findings suggest that eIC when compared with paper (1) did not increase technology burden, (2) supported comparable comprehension, (3) upheld key elements of participant agency, and (4) increased completion of mandatory consent fields. The results support a broader call for organizations to offer eIC for clinical research discussions to enhance the overall participant experience and increase the completeness of the consent process.

Purpose: Our institution participated in the Oncology Care Model, which required us to include many of the 13 elements of the National Academy of Medicine (NAM) care plan into care pathways for our patients. We optimized our existing chemotherapy consent process to meet this need and maximized completion., Methods: Our multidisciplinary committee developed a three-phase Plan-Do-Study-Act process in our breast cancer clinic: (1) update and educate providers on our paper chemotherapy form with multiple components of the NAM care plan including prognosis and treatment effects on quality of life; (2) piloted an electronic chemotherapy consent form to decrease the administrative burden; and (3) autopopulated fields within the electronic consent. We assessed feedback after cycle 1 and created a Pareto chart. The outcome measure was percent completion of chemotherapy consent documents., Results: Baseline monthly random chart audit of 40 patients revealed 20% of paper chemotherapy consent forms were completed in their entirety among patients. When we re-educated clinicians about the new paper consent containing the NAM elements, compliance rose to nearly 30%. A Pareto chart confirmed that content redundancy and wordiness were leading to under-completion. After creating and piloting the electronic consent, compliance increased to 90%. Finally, autopopulation with drop-down selections increased and sustained completion to 100%., Conclusion: Incorporating regulatory requirements into an existing workflow using Plan-Do-Study-Act methodology can reduce administrative burden on clinicians. Additional use of innovative technology can further increase clinician compliance with regulatory requirements while delivering high-value quality care to patients with cancer., Competing Interests: Cardinale B. SmithConsulting or Advisory Role: Bristol Myers SquibbSpeakers' Bureau: Teva Mark LiuConsulting or Advisory Role: Bristol Myers SquibbNo other potential conflicts of interest were reported.

Purpose: The burden of cancer disproportionately affects low- and middle-income countries. Low 5-year survival figures for children with cancer in low-income countries are due to late presentation at diagnosis, treatment abandonment, absence of sophisticated multidisciplinary care, and lack of adequate resources. The reasons for late presentation are partly due to limited awareness of cancer symptoms, high treatment costs, and facility-level barriers to timely access to treatment. Given the systemic challenges, the regional need for palliative oncology care for children care is high. Despite the enormity of the need for palliative oncology for children with cancer in Africa, its level of development remains poor. This paper presents the evidence on the status of palliative oncology care for children in sub-Saharan Africa., Methods: This review provides an overview of the current status of palliative oncology care for children in sub-Saharan Africa, using the WHO building blocks for health systems strengthening as reference points, before proposing a forward-looking prioritized agenda for its development., Results: We noted that survival rates for children with cancer remain much poorer in Africa compared with developed countries and palliative oncology care resources are scant. Our results also show low coverage for palliative oncology care services for children, lack of a critical mass of health workers with the skills to deliver the care, a lack of robust documentation of the burden of cancer, widespread lack of access to essential controlled medicines, limited funding from government and limited coverage for palliative oncology care in most cancer control plans., Conclusion: This review highlights priority areas for action that align to the WHO health system building blocks for strengthening health systems., Competing Interests: Vivienne MulemaConsulting or Advisory Role: Beyond Logistics LimitedNo other potential conflicts of interest were reported.

Recognizing the increase in cancer incidence globally and the need for effective cancer control interventions, several organizations, professional bodies, and international institutions have proposed strategies to improve treatment options and reduce mortality along with minimizing overall incidence. Despite these efforts, an estimated 9.6 million deaths in 2018 was attributed to this noncommunicable disease, making it the second leading cause of death worldwide. Left unchecked, this will further increase in scale, with an estimated 29.5 million new cases and 16.3 million deaths occurring worldwide in 2040. Although it is known and generally accepted that cancer services must include radiotherapy, such access is still very limited in many parts of the world, especially in low- and middle-income countries. After thorough review of the current status of radiotherapy including programs worldwide, as well as achievements and challenges at the global level, the International Atomic Energy Agency convened an international group of experts representing various radiation oncology societies to take a closer look into the current status of radiotherapy and provide a road map for future directions in this field. It was concluded that the plethora of global and regional initiatives would benefit further from the existence of a central framework, including an easily accessible repository through which better coordination can be done. Supporting this framework, a practical inventory of competencies needs to be made available on a global level emphasizing the knowledge, skills, and behavior required for a safe, sustainable, and professional practice for various settings. This white paper presents the current status of global radiotherapy and future directions for the community. It forms the basis for an action plan to be developed with professional societies worldwide., Competing Interests: Arthur Accioly RosaEmployment: Grupo OncoclinicasHonoraria: RocheConsulting or Advisory Role: AstraZenecaTravel, Accommodations, Expenses: Roche Yolande LievensConsulting or Advisory Role: AstraZenecaSpeakers' Bureau: RaySearch Laboratories Stephen HahnEmployment: BlackfynnLeadership: BlackfynnStock and Other Ownership Interests: BlackfynnConsulting or Advisory Role: BlackfynnPatents, Royalties, Other Intellectual Property: Biolytech—patent in underlying technology; co-holder of patent until one year ago. Now held by my non-dependent adult children Mary GospodarowiczHonoraria: IBANo other potential conflicts of interest were reported.

A paper analytic device, the chemoPAD, was developed and validated to visually detect methotrexate, doxorubicin, cisplatin, and oxaliplatin at concentrations commonly found in injectable dosage forms. By testing residual solution after patient treatment, the chemoPAD can be used to monitor drug quality without restriction of patient access to medication. The chemoPAD is produced by wax printing on Ahlstrom paper to create separate reaction areas and deposits small amounts of chemicals to create color changes in response to different active pharmaceutical ingredients (APIs). This creates a unique color bar code to identify each medication. Internal validation studies show that the chemoPAD has excellent sensitivity and specificity to differentiate between samples of 100% and 0% API, which is the distinction relevant to the majority of reported falsified chemotherapy cases. The platinum-containing drugs, cisplatin and oxaliplatin, can be detected semiquantitatively. The cards can be read either visually by comparison with a standard image or by using computer image analysis. Dosage forms were collected from the Ethiopian health care system and analyzed with the chemoPAD followed by high-performance liquid chromatography. A substandard sample was discovered and reported to the Ethiopian Food Medicine and Healthcare Administration and Control Authority. [ABSTRACT FROM AUTHOR]

PURPOSE: Digital technologies create opportunities for improving consenting processes in cancer care and research. Yet, little is known about the prevalence of electronic consenting, or e-consent, at US cancer care institutions. METHODS: We surveyed institutions in the National Comprehensive Cancer Network about their capabilities for clinical, research, and administrative e-consents; technologies used; telemedicine consents; multilingual support; evaluations; and opportunities and challenges in moving from paper-based to electronic processes. Responses were summarized across responding institutions. RESULTS: Twenty-five institutions completed the survey (81% response rate). Respondents were from all census regions and included freestanding and matrix cancer centers. Twenty (80%) had e-consent capabilities, with variability in the extent of adoption: One (5%) had implemented e-consent for all clinical, research, and administrative needs while 19 (95%) had a mix of paper and electronic consenting. Among those with e-consent capabilities, the majority (14 of 20, 70%) were using features embedded in their electronic health record. Most had a combination of paper and e-consenting for clinical purposes (18, 72%). About two-thirds relied entirely on paper for research consents (16, 64%) but had at least some electronic processes for administrative consents (15, 60%). Obstacles to e-consenting included challenges with procuring or maintaining hardware, content management, workflow integration, and digital literacy of patients. Successes included positive user experiences, workflow improvements, and better record-keeping. Only two of 20 (10%) respondents with e-consent capabilities had evaluated the impact of automating consent processes. CONCLUSION: E-consent was prevalent in our sample, with 80% of institutions reporting at least some capabilities. Further progress is needed for the benefits of e-consenting to be realized broadly. Digital technologies can improve consenting processes. We surveyed National Comprehensive Cancer Network member institutions about electronic consenting capabilities and experiences. Twenty-five (81%) completed the survey. Twenty (80%) had e-consent capabilities, mostly embedded in their electronic health record (14, 70%). One (5%) had e-consent for all clinical, research, and administrative needs while 19 (95%) had a mix of paper and e-consenting. Obstacles included challenges procuring/maintaining hardware, content management, workflow integration, and patients' digital literacy. Successes included user satisfaction, workflow improvements, and better record-keeping. Only two had formally evaluated their e-consent processes. Further progress is needed to broadly realize e-consent's benefits. [ABSTRACT FROM AUTHOR]

Progress toward improvement in cancer therapy relies on clinical trials. Yet, only a minority of eligible patients with cancer enroll as a result of multiple barriers at the patient, investigator, center, and national level. However, the rise of the Internet and mobile technology has created a slew of tools with medical applications, from Web sites to apps to social media platforms, all of which may aide clinicians in our quest to improve the clinical research enterprise. SWOG is one of five members in the National Cancer Institute's National Clinical Trials Network-the nation's oldest and largest publicly funded cancer research network-and is taking a leadership role in exploring and testing the promise of digital engagement through the empaneling of the Digital Engagement Committee. This article outlines the mission, principles, and priorities of the Digital Engagement Committee and proposes how this work may inform the use of digital tools for the cancer research community and, hopefully, translate to improved outcomes for our patients.

Aging is a heterogeneous process. Most newly diagnosed cancers occur in older adults, and it is important to understand a patient's underlying health status when making treatment decisions. A geriatric assessment provides a detailed evaluation of medical, psychosocial, and functional problems in older patients with cancer. Specifically, it can identify areas of vulnerability, predict survival and toxicity, assist in clinical treatment decisions, and guide interventions in routine oncology practice; however, the uptake is hampered by limitations in both time and resources, as well as by a lack of expert interpretation. In this review, we describe the utility of geriatric assessment by using an illustrative case and provide a practical approach to geriatric assessment in oncology.

Purpose: Advances in germline genetics, and related therapeutic opportunities, present new opportunities and challenges in prostate cancer. The Prostate Cancer Clinical Trials Consortium Germline Genetics Working Group was established to address genetic testing for men with prostate cancer, especially those with advanced disease undergoing testing for treatment-related objectives and clinical trials., Methods: The Prostate Cancer Clinical Trials Consortium Germline Genetics Working Group met monthly to discuss the current state of genetic testing of men with prostate cancer for therapeutic or clinical trial purposes. We assessed current institutional practices, developed a framework to address unique challenges in this population, and identified areas of future research., Results: Genetic testing practices in men with prostate cancer vary across institutions; however, there were several areas of agreement. The group recognized the clinical benefits of expanding germline genetic testing, beyond cancer risk assessment, for the goal of treatment selection or clinical trial eligibility determination. Genetic testing for treatment selection should ensure patients receive appropriate pretest education and consent and occur under auspices of a research study whenever feasible. Providers offering genetic testing should be able to interpret results and recommend post-test genetic counseling for patients. When performing tumor (somatic) genomic profiling, providers should discuss the potential for uncovering germline mutations and recommend appropriate genetic counseling. In addition, family members may benefit from cascade testing and early cancer screening and prevention strategies., Conclusion: As germline genetic testing is incorporated into practice, further development is needed in establishing prompt testing for time-sensitive treatment decisions, integrating cascade testing for family, ensuring equitable access to testing, and elucidating the role of less-characterized germline DNA damage repair genes, individual gene-level biologic consequences, and treatment response prediction in advanced disease., Competing Interests: AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/po/author-center.

Aging is a heterogeneous process. Most newly diagnosed cancers occur in older adults, and it is important to understand a patient's underlying health status when making treatment decisions. A geriatric assessment provides a detailed evaluation of medical, psychosocial, and functional problems in older patients with cancer. Specifically, it can identify areas of vulnerability, predict survival and toxicity, assist in clinical treatment decisions, and guide interventions in routine oncology practice; however, the uptake is hampered by limitations in both time and resources, as well as by a lack of expert interpretation. In this review, we describe the utility of geriatric assessment by using an illustrative case and provide a practical approach to geriatric assessment in oncology. [ABSTRACT FROM AUTHOR]

PURPOSE: Inefficiencies in the clinical trial infrastructure result in protracted trial completion timelines, physician-investigator turnover, and a shrinking skilled labor force and present obstacles to research participation. Taken together, these barriers hinder scientific progress. Technological solutions to improve clinical trial efficiency have emerged, yet adoption remains slow because of concerns with cost, regulatory compliance, and implementation. METHODS: A prospective pilot study that compared regulatory-compliant digital and traditional wet ink paper signatures was conducted over a 6.5-month period in a hospital-based health system. Staff time and effort, error rate, costs, and time to completion were measured. Wilcoxon rank sum tests were used to compare staff time and time to completion. A value analysis was conducted. A survey was administered to measure user satisfaction. RESULTS: There where 96 participants (47 digital, 49 paper), 132 studies included (31 digital, 101 paper), and 265 documents processed (156 digital, 109 paper). A moderate reduction in staff time required to prepare documents for signature was observed (P <.0001). Error rates were reported in 5.1% of digital and 2.8% of paper documents, but this difference was not significant. Discrepancies requiring revisions included incomplete mandatory fields, inaccurate information submitted, and technical issues. A value analysis demonstrated a 19% labor savings with the use of digital signatures. Survey response rate was 57.4% (n = 27). Most participants (85.2%) preferred digital signatures. The time to complete documents was faster with digital signatures compared with paper (P =.0241). CONCLUSION: The use of digital signatures resulted in a decrease in document completion time and regulatory burden as represented by staff hours. Additional cost and time savings and information liquidity could be realized by integrating digital signatures and electronic document management systems. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate alternative automated methods of collecting data on quality of life (QOL) in cancer patients. After initial evaluation of a range of technologies, we compared computer touch-screen questionnaires with paper questionnaires scanned by optical reading systems in terms of patients' acceptance, data quality, and reliability., Patients and Methods: In a randomized cross-over trial, 149 cancer patients completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30, version 2.0 (EORTC QLQ-C30), and the Hospital Anxiety and Depression Scale (HADS) on paper and on a touch screen. In a further test-retest study, 81 patients completed the electronic version of the questionnaires twice, with a time interval of 3 hours between questionnaires., Results: Fifty-two percent of the patients preferred the touch screen to paper; 24% had no preference. The quality of the data collected with the touch-screen system was good, with no missed responses. At the group level, the differences between scores obtained with the two modes of administration of the instruments were small, suggesting equivalence for most of the QOL scales, with the possible exception of the emotional, fatigue, and nausea/vomiting scales and the appetite item, where patients tended to give more positive responses on the touch screen. At the individual patient level, the agreement was good, with a kappa coefficient from 0.57 to 0.77 and percent global agreement from 61% to 97%. The electronic questionnaire had good test-retest reliability, with correlation coefficients between the two administrations from 0.78 to 0.95, kappa coefficients of agreement from 0.55 to 0.90, and percent global agreement from 56% to 100%., Conclusion: Computer touch-screen QOL questionnaires were well accepted by cancer patients, with good data quality and reliability.

Background: Cigarettes are the biggest threat in the world, including Indonesia. According to The Health Ministry of Indonesia 2017 , Indonesia is one the country with the highest number of smokers. More than one-third (36.3%) of Indonesia's population, 20% are adolescents aged 13-15 years old. In Indonesia, cigarettes caused more than 200,000 deaths per year. It has been recorded that the amount of cigarettes consumed in Indonesia increases from 182 billion in 2001 to 260.8 billion in 2009. In addition to the increasing number of the smokers and the age of smoking, there is another factor which is adolescents deceit for their smoking behavior, therefore screening is necessary to prevent the complications from smoking. Aim: To find out changes in salivary pH as a smoking behavior screening tool in adolescents. Methods: : Results: Distribution of data in 85 samples with 50 nonsmokers and 35 smokers, got the youngest age of smoking is in fourth year of elementary school, with the highest number of cigarettes consumed per day is more than 2 boxes. The salivary pH in smokers was significantly (P < 0.005) lower than nonsmokers. This can be seen also through since the smoke, the last time smoking and the number of cigarettes consumed per day. The younger age of smoking, the last time smoking (<24 hour) and the more the number of cigarettes consumed per day, that all can significantly decrease salivary pH. Conclusion: Salivary pH measurement using litmus paper is a potential screening for smoking behavior in adolescents. [ABSTRACT FROM AUTHOR]

Purpose: Immediate transfer of patient-reported outcome measures (PROMs) for use in medical consultations is facilitated by electronic assessments. We aimed to describe the rationale and development of Eir version 3 (EirV3), a computer-based symptom assessment tool for cancer, with emphasis on content and user-friendliness. Methods: EirV3's specifications and content were developed through multiprofessional, stepwise, and iterative processes (from 2013 to 2016), with literature reviews on traditional and electronic assessment and classification methods, formative iterative usability tests with end-users, and assessment of patient preferences for paper versus electronic assessments. Results: EirV3 has the following two modules: Eir-Patient for PROMs registration on tablets and Eir-Doctor for presentation of PROMs in a user-friendly interface on computers. Eir-Patient starts with 19 common cancer symptoms followed by specific, in-depth questions for endorsed symptoms. The pain section includes a body map for pain location and intensity, whereas physical functioning, nutritional intake, and well-being are standard questions for all. Data are wirelessly transferred to Eir-Doctor. Symptoms with intensity scores ≥ 3 (on a 0 to 10 scale) are marked in red, with brighter colors corresponding to higher intensity, and supplemented with graphs displaying symptom development over time. Usability results showed that patients and health care providers found EirV3 to be intuitive, easy to use, and relevant. When comparing PROM assessments on paper versus tablets (n = 114), 19% of patients preferred paper, 41% preferred tablets, and 40% had no preference. Median intraclass correlation coefficient between paper and tablets (0.815) was excellent. Conclusion: Iterative test rounds followed by continuous improvements led to a user-friendly, applicable symptom assessment tool, EirV3, developed for and by end-users. EirV3 is undergoing international testing of clinical and cross-cultural adaptability. [ABSTRACT FROM AUTHOR]

Purpose: With the shift in the majority of oncology clinical care in the United States from paper records to electronic health records, researchers need efficient and validated processes to obtain accurate data about the entire treatment history of patients diagnosed with cancer. The objective of this study was to develop and validate an algorithm that is agnostic to the source of data but that can identify specific regimens in the entire course of systemic therapy treatment for patients diagnosed with breast, colorectal, or lung cancer. Methods: A cohort of patients with incident breast, colorectal, and lung cancer were randomly distributed into six groups. The algorithm was iteratively modified, and the performance was assessed until no additional modifications could be identified in the first three groups. The performance of the algorithm was confirmed in the three groups that remained. Results: The final model produced ranges of sensitivity between 97.2% and 100% for first-course systemic therapy across all cancers, with a false-positive rate of 0%. The algorithm matched the exact number of courses and the exact regimens of systemic therapy agents as captured by infusion, pharmacy, and procedure electronic medical record data for all courses of therapy 88% to 100% of the time. Conclusion: Use of our validated algorithm that characterizes entire courses of systemic therapy treatment in patients diagnosed with breast, colorectal, and lung cancer will allow researchers in a variety of settings to conduct comparative effectiveness studies related to the uptake, safety, outcomes, and costs associated with the use of both novel and standard regimens. [ABSTRACT FROM AUTHOR]

Guidelines are proposed for the reporting of clinical trials. These are meant to be used for both authors and journal editors. Specific proposals are made for: reporting the population under study, actual therapy used, describing the study design, accounting of patients, follow-up statistics, and describing the quality control of the data. Nonrandomized studies require special discussion. Such studies potentially have substantial biases which can lead to incorrect conclusions. Six areas of biases arising in nonrandomized studies are pointed out which should require a discussion in an acceptable published paper. The presentation of statistical results and the reporting of early studies present unusually difficult problems. Guidelines are presented for statistical analyses which, although simple to implement in practice, are not generally used. A proposal is made for the publication of early results of a study which require that the authors agree to follow and periodically report on their trial to the journal editor. If the early conclusions change with additional follow-up, the editor should notify its readers. The adoption of these guidelines can be an important force in raising the scientific level of the reporting of clinical trials.

Amount raised: During 2017, funds from Chai for Cancer Addas totaled approximately US$ 28,000 (IRS 18 lacs). Background and context: Chai for Cancer (www.chaiforcancer.org) is in a sense, a satellite brand of Friends of Max (www.friendsofmax.info). Friends of Max is a registered Public Charitable Trust and the support group arm of The Max Foundation in India. In India chai or tea is a household drink. At its best in an informal setting, an Adda serves a dual purpose as a fund-raiser and advocacy platform. It is based on the concept of an informal gathering among well-wishers and caregivers supporting underserved cancer patients suffering from chronic myeloid leukemia (CML) and gastrointestinal stromal tumor (GIST). The chronic condition is made manageable by life-long treatment. Aim: Chai For Cancer is a dynamic fundraiser and advocacy model for CML/GIST patients and caregivers in India. Strategy/Tactics: In 4 years, now on the cusp of the 5th year, Chai for Cancer has built up a creditable legacy of trust and an extended family of volunteers that networks throughout the year with the ability to attract new segments of donors/well-wishers and patient/caregiver participants. Funds thus raised support patient group meetings which facilitate various patient-related activities and patient–physician interactions which form the bedrock of FOM's dictum "Together We Share And Learn". Potential donors are approached and educated informally about how to host an Adda. Once the host expresses interest, support is provided to the host in terms of tea bags and paper cups (from Society Tea), literature (printed leaflets, brochures elaborating the concept, newsletters) and receipts (U/s 80 G of the Indian Income Tax Act, 1961). Program process: An Adda is usually hosted by members/volunteers belonging to Friends of Max although it is not unusual for persons who have simply heard of Chai for Cancer to get in touch and express interest in hosting an Adda. The emergence of new hosts like D Y Patil University and IDEAL (Institute of Design Expression Art and Learning) in Ahmedabad, Jayanth Jayaprakash's India To Excellence 2020 in addition to long-time supporters Society Tea, Being Human-The Salman Khan Foundation, Manish Mandhana Retail Ventures, Mahotsaav Entertainment, Radio One and Red FM is testimony to the strength of the fundraising/advocacy model and a platform to encourage openness, empowering patients and caregivers. HNIs from various industries have also been donors. Costs and returns: The entire process is manned by senior, experienced people who volunteer their time and professional skills. Year-long publicity is generated through social media (FM radio stations, Web site www.chaiforcancer.org Twitter, Instagram and Facebook). What was learned: This is a personalised and intimate approach to raising funds for patient-related activity. This approach ensures known and accepted sources of funds within a growing family. It is different from crowd-funding techniques. [ABSTRACT FROM AUTHOR]

PURPOSE: The specific aims of this paper are to (1) develop and operationalize an electronic health record (EHR) data quality framework, (2) apply the dimensions of the framework to the phenotype and treatment pathways of ductal carcinoma in situ (DCIS) using All of Us Research Program data, and (3) propose and apply a checklist to evaluate the application of the framework. METHODS: We developed a framework of five data quality dimensions (DQD; completeness, concordance, conformance, plausibility, and temporality). Participants signed a consent and Health Insurance Portability and Accountability Act authorization to share EHR data and responded to demographic questions in the Basics questionnaire. We evaluated the internal characteristics of the data and compared data with external benchmarks with descriptive and inferential statistics. We developed a DQD checklist to evaluate concept selection, internal verification, and external validity for each DQD. The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) concept ID codes for DCIS were used to select a cohort of 2,209 females 18 years and older. RESULTS: Using the proposed DQD checklist criteria, (1) concepts were selected and internally verified for conformance; (2) concepts were selected and internally verified for completeness; (3) concepts were selected, internally verified, and externally validated for concordance; (4) concepts were selected, internally verified, and externally validated for plausibility; and (5) concepts were selected, internally verified, and externally validated for temporality. CONCLUSION: This assessment and evaluation provided insights into data quality for the DCIS phenotype using EHR data from the All of Us Research Program. The review demonstrates that salient clinical measures can be selected, applied, and operationalized within a conceptual framework and evaluated for fitness for use by applying a proposed checklist. A Data Quality Framework Applied to ductal carcinoma in situ EHR data. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most common cancer among women in developed and developing countries. In Poland during last three decades BC incidence has doubled. Accordingly to the latest epidemiologic data from the National Cancer Registry in Poland, 2015 was another year with BC incidence increase - 18 106 new cases of BC (age standardized rate/100 000 - 90.9). Moreover, BC is the second leading cause of cancer mortality among women in Poland (14.1% of deaths). As we still don't have sufficient knowledge about BC origin, it is crucial to limit well-known risk factors of BC to reduce number of new cases. To achieve this significant public health goal there is a need to identify and understand women's attitudes and measure their knowledge about protective and risk factors in BC, especially among women in the age of 45 years old and older, which is the most prone group. Aim: To analyze women's attitudes and investigate their knowledge about BC risk and protective factors in the age group 45 years old and older in Poland. Methods: Data from 380 women were collected from May to August 2017 in Poland. Women from this cohort were randomly selected from whole country and included healthy women, women with BC and convalescent women after BC and other types of cancer. The basic inclusion criterion was age of the women - at least 45 y.o. at the moment of the study. As a tool for data collection, original questionnaire has been projected and implemented, both in electronic and paper version. Questionnaire has been divided into following sections: BC completed treatment, education about BC and prophylaxis (BC risk factors) and consisted from 26 questions single and multiple choice. Collected data has been preliminarily analyzed by Microsoft Excel (v. 14.0.7173.5000), taking also into account sociodemographic profile of women from the research group. Results: 43% (166) of women had completed higher education, 49% (187) secondary education (eg high school) and 2% (8) basic education. Among women with the highest level of education 40% (67) had BC, 60% (99) didn't. In the group of women with secondary education it was respectively 72% (137) and 26% (50) and in the group with basic education 87.5% (7) and 12.5% (1). 52% (196) of women completed education about BC risk factors prophylaxis in the past (lectures, courses, etc.). In this group 70% (135) of respondents claim that this education improved their level of knowledge. Among this women, 28% (38) claim that alcohol consumption contributes to BC, 37% (50) - hormonal replacement therapy, 47% (63) - overweight and obesity and 64% (87) - gene mutations - BRCA1 and BRCA2. Conclusion: Study results suggest that there is a need to create and implement coordinated actions aiming education about BC risk factors among women 45+, which is the most prone group. As we still don't have all answers about BC origin, efficient health education seems to be the best way to decrease BC incidence. [ABSTRACT FROM AUTHOR]

PURPOSE: Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk prediction models have been developed using retrospective clinical data and have evolved significantly over the years in terms of predictors of recurrence, data usage, and predictive techniques (statistical/machine learning [ML]). METHODS: Following PRISMA guidelines, we performed a systematic literature review of the aforementioned statistical and ML models published between January 2008 and December 2022 through searching five digital databases—PubMed, ScienceDirect, Scopus, Cochrane, and Web of Science. The comprehensive search yielded a total of 163 papers and after a screening process focusing on papers that dealt exclusively with statistical/ML methods, only 23 papers were deemed appropriate for further analysis. We benchmarked the studies on the basis of development, evaluation metrics, and validation strategy with an added emphasis on racial diversity of patients included in the studies. RESULTS: In total, 30.4% of the included studies use statistical techniques, while 69.6% are ML-based. Among these, traditional ML models (support vector machines, decision tree, logistic regression, and naïve Bayes) are the most frequently used (26.1%) along with deep learning (26.1%). Deep learning and ensemble learning provide the most accurate predictions (AUC = 0.94 each). CONCLUSION: ML-based prediction models exhibit outstanding performance, yet their practical applicability might be hindered by limited interpretability and reduced generalization. Moreover, predictive models for BC recurrence often focus on limited variables related to tumor, treatment, molecular, and clinical features. Imbalanced classes and the lack of open-source data sets impede model development and validation. Furthermore, existing models predominantly overlook African and Middle Eastern populations, as they are trained and validated mainly on Caucasian and Asian patients. We traced the advancement of breast cancer recurrence risk prediction models published between 2008 and 2022 in a systematic way that includes both statistical and artificial intelligence models. This review article serves as a guide for practitioners, offering valuable insights on how to effectively incorporate predictive tools into clinical practice. Moreover, it provides researchers with valuable feedback and recommendations to further improve and refine the predictive models. [ABSTRACT FROM AUTHOR]

PURPOSE: To evaluate natural language processing (NLP) methods to infer metastatic sites from radiology reports. METHODS: A set of 4,522 computed tomography (CT) reports of 550 patients with 14 types of cancer was used to fine-tune four clinical large language models (LLMs) for multilabel classification of metastatic sites. We also developed an NLP information extraction (IE) system (on the basis of named entity recognition, assertion status detection, and relation extraction) for comparison. Model performances were measured by F1 scores on test and three external validation sets. The best model was used to facilitate analysis of metastatic frequencies in a cohort study of 6,555 patients with 53,838 CT reports. RESULTS: The RadBERT, BioBERT, GatorTron-base, and GatorTron-medium LLMs achieved F1 scores of 0.84, 0.87, 0.89, and 0.91, respectively, on the test set. The IE system performed best, achieving an F1 score of 0.93. F1 scores of the IE system by individual cancer type ranged from 0.89 to 0.96. The IE system attained F1 scores of 0.89, 0.83, and 0.81, respectively, on external validation sets including additional cancer types, positron emission tomography-CT ,and magnetic resonance imaging scans, respectively. In our cohort study, we found that for colorectal cancer, liver-only metastases were higher in de novo stage IV versus recurrent patients (29.7% v 12.2%; P <.001). Conversely, lung-only metastases were more frequent in recurrent versus de novo stage IV patients (17.2% v 7.3%; P <.001). CONCLUSION: We developed an IE system that accurately infers metastatic sites in multiple primary cancers from radiology reports. It has explainable methods and performs better than some clinical LLMs. The inferred metastatic phenotypes could enhance cancer research databases and clinical trial matching, and identify potential patients for oligometastatic interventions. Ever thought of using NLP to extract sites of metastases from radiology reports? Read this paper. [ABSTRACT FROM AUTHOR]

PURPOSE: Real-world evidence (RWE)—derived from analysis of real-world data (RWD)—has the potential to guide personalized treatment decisions. However, because of potential confounding, generating valid RWE is challenging. This study demonstrates how to responsibly generate RWE for treatment decisions. We validate our approach by demonstrating that we can uncover an existing adjuvant chemotherapy (ACT) guideline for stage II and III colon cancer (CC)—which came about using both data from randomized controlled trials and expert consensus—solely using RWD. METHODS: Data from the population-based Netherlands Cancer Registry from a total of 27,056 patients with stage II and III CC who underwent curative surgery were analyzed to estimate the overall survival (OS) benefit of ACT. Focusing on 5-year OS, the benefit of ACT was estimated for each patient using G-computation methods by adjusting for patient and tumor characteristics and estimated propensity score. Subsequently, on the basis of these estimates, an ACT decision tree was constructed. RESULTS: The constructed decision tree corresponds to the current Dutch guideline: patients with stage III or stage II with T stage 4 should receive surgery and ACT, whereas patients with stage II with T stage 3 should only receive surgery. Interestingly, we do not find sufficient RWE to conclude against ACT for stage II with T stage 4 and microsatellite instability-high (MSI-H), a recent addition to the current guideline. CONCLUSION: RWE, if used carefully, can provide a valuable addition to our construction of evidence on clinical decision making and therefore ultimately affect treatment guidelines. Next to validating the ACT decisions advised in the current Dutch guideline, this paper suggests additional attention should be paid to MSI-H in future iterations of the guideline. This article demonstrates the value of real-world evidence in constructing a treatment guideline. [ABSTRACT FROM AUTHOR]

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials. This paper by the RECIST Working Group outlines a path to realize the potential of radiomics as a precision biomarker. [ABSTRACT FROM AUTHOR]

PURPOSE: Increasing use of immune checkpoint inhibitors (ICIs) in routine cancer care will increase the incidence of immune-related adverse events (irAEs). Systems are needed to support remote monitoring for irAEs. Electronic patient-reported outcome (ePRO) symptom monitoring systems can help monitor and manage symptoms and side effects. We assessed the content and features of ePRO symptom monitoring systems for irAEs, and their feasibility, acceptability, and impact on patient outcomes and health care utilization. METHODS: A systematic literature search was conducted in May 2022 on MEDLINE, Embase, PsycINFO, and Cochrane Central Register of Controlled Trials. Quantitative and qualitative data relevant to the review questions were extracted and synthesized in tables. RESULTS: Seven papers describing five ePRO systems were included. All systems collected PROs between clinic visits. Two of five used validated symptom questionnaires, 3/5 provided prompts to complete questionnaires, 4/5 provided reminders to self-report, and 3/5 provided clinician alerts for severe/worsening side effects. Four of five provided coverage of ≥26/30 irAEs in the ASCO irAE guideline. Feasibility and acceptability were demonstrated with consent rates of 54%-100%, 17%-27% of questionnaires generating alerts, and adherence rates of 74%-75%. One paper showed a reduction in grade 3-4 irAEs, treatment discontinuation, clinic visit duration, and emergency department presentations, while another showed no difference in these outcomes or the rate of steroid use. CONCLUSION: There is preliminary evidence of the feasibility and acceptability of ePRO symptom monitoring for irAEs. However, further studies are needed to confirm the impact on ICI-specific outcomes, such as the frequency of grade 3-4 irAEs and duration of immunosuppression. Suggestions for the content and features of future ePRO systems for irAEs are provided. [ABSTRACT FROM AUTHOR]

PURPOSE: Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning (ML) methods enable researchers to extract characteristics from unstructured clinical notes, and represent a more cost-effective and scalable approach than manual expert abstraction. These extracted data are then used in epidemiologic or statistical models as if they were abstracted observations. Analytical results derived from extracted data in this way may differ from those given by abstracted data, and the magnitude of this difference is not directly informed by standard ML performance metrics. METHODS: In this paper, we define the task of postprediction inference, which is to recover similar estimation and inference from an ML-extracted variable that would be obtained from abstracting the variable. We consider fitting a Cox proportional hazards model that uses a binary ML-extracted variable as a covariate and evaluate four approaches for postprediction inference in this setting. The first two approaches only require the ML-predicted probability, while the latter two additionally require a labeled (human abstracted) validation data set. RESULTS: Our results for both simulated data and EHR-derived RWD from a national cohort demonstrate that we can improve inference from ML-extracted variables by leveraging a limited amount of labeled data. CONCLUSION: We describe and evaluate methods for fitting statistical models using ML-extracted variables subject to model error. We show that estimation and inference is generally valid when using extracted data from high-performing ML models. More complex methods that incorporate auxiliary labeled data provide further improvements. This paper develops novel methodology for using ML-extracted variables in statistical analyses. [ABSTRACT FROM AUTHOR]

Clinical genomic testing of patient germline, tumor tissue, or plasma cell-free DNA can enable a personalized approach to cancer management and treatment. In prostate cancer (PCa), broad genotyping tests are now widely used to identify germline and/or somatic alterations in BRCA2 and other DNA damage repair genes. Alterations in these genes can confer cancer sensitivity to poly (ADP-ribose) polymerase inhibitors, are linked with poor prognosis, and can have potential hereditary cancer implications for family members. However, there is huge variability in genomic tests and reporting standards, meaning that for successful implementation of testing in clinical practice, end users must carefully select the most appropriate test for a given patient and critically interpret the results. In this white paper, we outline key pre- and post-test considerations for choosing a genomic test and evaluating reported variants, specifically for patients with advanced PCa. Test choice must be based on clinical context and disease state, availability and suitability of tumor tissue, and the genes and regions that are covered by the test. We describe strategies to recognize false positives or negatives in test results, including frameworks to assess low tumor fraction, subclonal alterations, clonal hematopoiesis, and pathogenic versus nonpathogenic variants. We assume that improved understanding among health care professionals and researchers of the nuances associated with genomic testing will ultimately lead to optimal patient care and clinical decision making. This article provides a helpful framework for choosing and interpreting a genomic test in prostate cancer. [ABSTRACT FROM AUTHOR]

PURPOSE: The way late-onset toxicities are managed can affect trial outcomes and participant safety. Specifically, participants often might not have completed their entire follow-up period to observe any toxicities before new participants would be recruited. We conducted a methodological review of published early-phase dose-finding clinical trials that used designs accounting for partial and complete toxicity information, aiming to understand (1) how such designs were implemented and reported and (2) if sufficient information was provided to enable the replicability of trial results. METHODS: Until March 26, 2023, we identified 141 trials using the rolling 6 design, the time-to-event continuous reassessment method (TITE-CRM), the TITE-CRM with cycle information, the TITE Bayesian optimal interval design, the TITE cumulative cohort design, and the rapid enrollment design. Clinical settings, design parameters, practical considerations, and dose-limiting toxicity (DLT) information were extracted from these published trials. RESULTS: The TITE-CRM (61, 43.3%) and the rolling 6 design (76, 53.9%) were most frequently implemented in practice. Trials using the TITE-CRM had longer DLT assessment windows beyond the first cycle compared with the rolling 6 design (52.5% v 6.6%). Most trials implementing the TITE-CRM (91.8%, 56 of 61) failed to describe essential parameters in the protocols or the study result papers. Only five TITE-CRM trials (8.2%, 5 of 61) reported sufficient information to enable replication of the final analysis. CONCLUSION: When compared with trials using the rolling 6 design, those implementing the TITE-CRM design exhibited notable deficiencies in reporting essential details necessary for reproducibility. Inadequate reporting quality of advanced model-based trial designs hinders their credibility. We provide recommendations that can improve transparency, reproducibility, and accurate interpretation of the results for such designs. Evaluated late-onset toxicity-focussed dose-finding trials, recommending improved reporting practices [ABSTRACT FROM AUTHOR]

Paper describes our development of a web-based tool to make Medicare patient prices for cancer drugs known to their care teams. [ABSTRACT FROM AUTHOR]

PURPOSE: This discussion paper outlines challenges and proposes solutions for successfully implementing prediction models that incorporate patient-reported outcomes (PROs) in cancer practice. METHODS: We organized a full-day multidisciplinary meeting of people with expertise in cancer care delivery, PRO collection, PRO use in prediction modeling, computing, implementation, and decision science. The discussions presented here focused on identifying challenges to the development, implementation and use of prediction models incorporating PROs, and suggesting possible solutions. RESULTS: Specific challenges and solutions were identified across three broad areas. (1) Understanding decision making and implementation: necessitating multidisciplinary collaboration in the early stages and throughout; early stakeholder engagement to define the decision problem and ensure acceptability of PROs in prediction; understanding patient/clinician interpretation of PRO predictions and uncertainty to optimize prediction impact; striving for model integration into existing electronic health records; and early regulatory alignment. (2) Recognizing the limitations to PRO collection and their impact on prediction: incorporating validated, clinically important PROs to maximize model generalizability and clinical engagement; and minimizing missing PRO data (resulting from both structural digital exclusion and time-varying factors) to avoid exacerbating existing inequalities. (3) Statistical and modeling challenges: incorporating statistical methods to address missing data; ensuring predictive modeling recognizes complex causal relationships; and considering temporal and geographic recalibration so that model predictions reflect the relevant population. CONCLUSION: Developing and implementing PRO-based prediction models in cancer care requires extensive multidisciplinary working from the earliest stages, recognition of implementation challenges because of PRO collection and model presentation, and robust statistical methods to manage missing data, causality, and calibration. Prediction models incorporating PROs should be viewed as complex interventions, with their development and impact assessment carried out to reflect this. Challenges and solutions to implementing patient-reported outcome–based predictive models in cancer. [ABSTRACT FROM AUTHOR]

PURPOSE Evidence supporting social media--based recruitment of cancer survivors is limited. This paper describes how we used Facebook during the COVID-19 pandemic to augment our recruitment of breast cancer survivors for our two-site telephone-based randomized clinical trial (RCT) at Dartmouth- Hitchcock Medical Center and the University of Alabama at Birmingham. METHODS Originally a two-site RCT of a telephone-delivered breast cancer survivorship intervention, we extended our clinic-based recruitment to Facebook. Participant characteristics, geographic reach, and baseline outcomes were compared across recruitment sources (ie, two clinics and Facebook) using descriptive statistics and effect sizes. RESULTS Enrollment rates (20%-29%) were comparable across recruitment sources. The 21-month Facebook marketing campaign accounted for 59% (n 5 179/303) of our total sample and had the greatest geographic reach, recruiting women from 24 states. The Facebook campaign reached a total of 51,787 unique individuals and cost $88.44 in US dollars (USD) per enrolled participant. Clinic samples had a greater proportion of women who were widowed (8% v 1%; P 5 .03) and Facebook had a higher proportion of women with a household income over $40,000 USD (83% v 71%; P 5 .02). There were no statistically significant differences between Facebook and the two clinics on baseline survey scores. CONCLUSION Augmenting traditional recruitment with Facebook increased our RCT's geographic and sociodemographic reach and supportedmeeting recruitment goals in a timely way. In the wake of the COVID-19 pandemic, cancer survivorship researchers should consider using social media as a recruitment strategy while weighing the advantages and potential biases introduced through such strategies. [ABSTRACT FROM AUTHOR]

PURPOSE: Patient portal technology offers important new opportunities to support person-centered clinician-patient communication. METHODS: Questionnaires relating to understanding of illness and treatment intent were sent quarterly via portal to all patients scheduled for follow-up in GI medical oncology clinics. For patients in selected clinics, items eliciting health-related values were added. Patient responses were available to all oncology team members in the electronic health record. Workflow and content of clinician-patient discussions about illness, treatment, and care goals stayed within clinicians' discretion. Feasibility (patient response rate), patient understanding, acceptability (three-item patient questionnaire), and efficacy (quality of clinician communication) were evaluated. RESULTS: From May 2021 through December 2022, a total of 12,233 questionnaires about illness/treatment understanding were sent to 6,325 patients (one to six per patient), with 97% response, including 9,358 with both open- and closed-ended responses. Fewer than 0.1% of patients indicated distress related to the questionnaire/process. Open-ended responses complemented closed-ended answers by revealing prognostic awareness and illness concerns. Of 48 patients approached to complete the full questionnaire including values items via portal, 15 first received and completed them in clinic (5 on iPad, 10 on paper), while 33 received and 27 (82%) completed the portal questionnaire. Patients found the portal process acceptable, and ratings of clinician communication were higher after clinic visits informed by patients' questionnaire responses (average prescore 6.8 v 5.9 post; P =.03). CONCLUSION: Almost all patients in this large GI cancer cohort responded via the portal about their understanding of illness and treatment goals. Eliciting their personal values by portal was also feasible, accepted by patients, and improved patient ratings of clinicians' communication. Portals represent a promising tool for scaling assessment of essential patient-reported elements of person-centered communication. Patient portals can help scale assessment of patient-reported elements of person-centered communication. [ABSTRACT FROM AUTHOR]

PURPOSE: Although there are commonly accepted criteria of what defines quality of health care including cancer care, less is known about what defines quality of mHealth interventions in health care. The aim of this review was to identify how quality of mHealth interventions for cancer survivors is described and measured. METHODS: CINAHL, EmCare, JBI, Medline, SCOPUS, and ProQuest databases from January 2008 to January 2020 were searched. Review papers with search terms related to mobile devices, quality, and cancer relevant to adults with cancer were included. Interventions needed to consist of mHealth technologies, such as mobile applications or short message service, or wearable devices. Title and abstract screening, full-text screening, and data extraction were performed independently by two reviewers. Conflicts were resolved by a third reviewer. Reviews were evaluated for coverage of quality according to six metrics defined by the Institute of Medicine: patient-centeredness, equitability, safety, effectiveness, timeliness, and efficiency. Any additional quality items were recorded. A Measurement Tool to Assess systematic Reviews (AMSTAR) was used to rate the quality of the reviews included. RESULTS: The initial search yielded 766 papers with seven systematic reviews meeting the eligibility criteria. Four papers were of AMSTAR moderate quality, with three of low quality. The median number of quality metrics reported in a review was two (the range was 1-4). Efficacy and safety and timeliness and efficiency were most reported (n = 4), followed by usability (n = 3), equitability and access (n = 2), privacy and security (n = 2), and patient-centeredness (n = 2). CONCLUSION: There is great variability in how quality of mHealth interventions is defined with no reviews addressing all quality metrics. A comprehensive approach to measure quality of mHealth interventions is needed. Quality metrics of mHealth interventions for cancer survivors: variable and limited—standards needed [ABSTRACT FROM AUTHOR]

PURPOSE: Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing antitumor efficacy. A publicly accessible biomedical literature search engine dedicated to this domain will facilitate knowledge discovery and reduce manual search and review. METHODS: We developed RetriLite, an information retrieval and extraction framework that leverages natural language processing and domain-specific knowledgebase to computationally identify highly relevant papers and extract key information. The modular architecture enables RetriLite to benefit from synergizing information retrieval and natural language processing techniques while remaining flexible to customization. We customized the application and created an informatics pipeline that strategically identifies papers that describe efficacy of using combination therapies in clinical or preclinical studies. RESULTS: In a small pilot study, RetriLite achieved an F 1 score of 0.93. A more extensive validation experiment was conducted to determine agents that have enhanced antitumor efficacy in vitro or in vivo with poly (ADP-ribose) polymerase inhibitors: 95.9% of the papers determined to be relevant by our application were true positive and the application's feature of distinguishing a clinical paper from a preclinical paper achieved an accuracy of 97.6%. Interobserver assessment was conducted, which resulted in a 100% concordance. The data derived from the informatics pipeline have also been made accessible to the public via a dedicated online search engine with an intuitive user interface. CONCLUSION: RetriLite is a framework that can be applied to establish domain-specific information retrieval and extraction systems. The extensive and high-quality metadata tags along with keyword highlighting facilitate information seekers to more effectively and efficiently discover knowledge in the combination therapy domain. [ABSTRACT FROM AUTHOR]

PURPOSE Cancer care guidelines recommend regular distress screening of patients, with approximately one in three patients with cancer experiencing significant distress. However, the implementation of such programs is variable and inconsistent. We sought to assess the feasibility of implementing a hybrid electronic and paper screening tool for distress in all patients coming to a large academic cancer center and an associated integrated network site. METHODS Patients at an academic cancer center (Stanford Cancer Center) and its associated integrated network site received either an electronic or on-paper modified Patient-Reported Outcomes Measurement Information System-Global Health questionnaire, to assess overall health and distress. We used the Reach, Effectiveness, Adoption, Implementation, and Maintenance implementation framework to test and report on the feasibility of using this questionnaire. Iterative workflow changes were made to implement the questionnaire throughout the healthcare system, including processes to integrate with existing electronic health records. RESULTS From June 2015 to December 2017, 53,954 questionnaires representing 26,242 patients were collected. Approximately 30% of the questionnaires were completed before the visit on an electronic patient portal. The number of patients meeting the positive screen threshold remained around 40% throughout the study period. Following assessment, there were 3,763 referrals to cancer supportive services. Of note, those with a positive screen were more likely to have a referral to supportive care (odds ratio, 6.4; 95% CI, 5.8 to 6.9; P < .0001). CONCLUSION The hybrid electronic and on-paper use of a commonly available patient-reported outcome tool, Patient-Reported Outcomes Measurement Information System-Global Health, as a large-scale distress screening method, is feasible at a large integrated cancer center. [ABSTRACT FROM AUTHOR]

The article is a response to a letter sent by Kempf et al. regarding a publication on the automatic detection of distant metastasis mentions in radiology reports in Spanish. The authors acknowledge the interest in their paper and discuss the importance of context in determining the metastatic status of a tumor. They compare their machine learning-based model to a rule-based algorithm and highlight the limitations of rule-based methods in imaging reports in Spanish. The authors also provide performance metrics for their model and discuss the annotation process of the corpus used in their study. They express their commitment to improving their model and methodology and invite further collaboration and discussion with the research community. [Extracted from the article]

PURPOSE: In 2014, the ASCO developed CancerLinQ (CLQ), a health technology platform for oncology. The CLQ Discovery (CLQD) database was created to make data available for research and this paper provides a summary of this database. METHODS: This study described the clinical and demographic characteristics of the 12 most common cancers in the CLQD database. We included patients with a new malignant tumor diagnosis between January 1, 2013, and December 31, 2018, of the following cancers: breast, lung and bronchus, prostate, colon and rectum, melanoma of the skin, bladder, non-Hodgkin lymphoma, kidney and renal pelvis, uterus, leukemia, pancreas, and thyroid. Patients with an in-situ diagnosis were excluded. Summary statistics and Kaplan-Meier survival estimates were calculated for each tumor. RESULTS: From 2013 to 2018, 491,360 patients were diagnosed with the study tumors. Breast cancer (139,506) was the most common, followed by lung and bronchus (70,959), prostate (63,303), and colon and rectum (53,504). The median age at diagnosis (years) was 61, 68, 68, and 64 in breast, lung and bronchus, prostate, and colon and rectum cohorts, respectively. Compared to the SEER 5-year overall survival estimates for several tumor types were higher in the CLQD database, possibly because of incomplete mortality capture in electronic health records. CONCLUSION: This paper presents the first description of the CLQD database since its inception. CLQ will continue to evolve over time, and the breadth and depth of this data asset will continue to grow. ASCO and CLQ's long-term goal is to improve the quality of patient care and create a sustainable database for oncology researchers. These results demonstrate that CLQ built a scalable database that can be used for oncology research. [ABSTRACT FROM AUTHOR]

PURPOSE: The Maine Cancer Genomics Initiative (MCGI) aimed to overcome patient- and provider-level barriers to using genomic tumor testing (GTT) in rural practices by providing genomic tumor boards (GTBs), clinician education, and access to comprehensive large-panel next-generation sequencing to all patients with cancer in Maine. This paper describes the successful implementation of the initiative and three key services made operative between 2016 and 2020. METHODS: A community-inclusive, hub-and-spoke approach was taken to implement the three program components: (1) a centralized GTB program; (2) a modular online education program, designed using an iterative approach with broad clinical stakeholders; and (3) GTT free of charge to clinicians and patients. Implementation timelines, participation metrics, and survey data were used to describe the rollout. RESULTS: The MCGI was launched over an 18-month period at all 19 oncology practices in the State. Seventy-nine physicians (66 medical oncologists, 5 gynecologic oncologists, 1 neuro-oncologist, and 7 pediatric oncologists) enrolled on the study, representing 100% of all practicing oncologists in Maine. Between July 2017 and September 2020, 1610 patients were enrolled. A total of 515 cases were discussed by 47 (73%) clinicians in 196 GTBs. Clinicians who participated in the GTBs enrolled significantly more patients on the study, stayed in Maine, and reported less time spent in clinical patient care. CONCLUSION: The MCGI was able to engage geographically and culturally disparate cancer care practices in a precision oncology program using a hub-and-spoke model. By facilitating access to GTT, structured education, and GTBs, we narrowed the gap in the implementation of precision oncology in one of the most rural states in the country. MCGI aimed to overcome patient- and provider-level barriers to GTT in rural practices by providing GTBs, clinician education, and access to large-panel NGS to all oncologists and their patients in Maine. [ABSTRACT FROM AUTHOR]

PURPOSE: Precision oncology mandates developing standardized common data models (CDMs) to facilitate analyses and enable clinical decision making. Expert-opinion–based precision oncology initiatives are epitomized in Molecular Tumor Boards (MTBs), which process large volumes of clinical-genomic data to match genotypes with molecularly guided therapies. METHODS: We used the Johns Hopkins University MTB as a use case and developed a precision oncology core data model (Precision-DM) to capture key clinical-genomic data elements. We leveraged existing CDMs, building upon the Minimal Common Oncology Data Elements model (mCODE). Our model was defined as a set of profiles with multiple data elements, focusing on next-generation sequencing and variant annotations. Most elements were mapped to terminologies or code sets and the Fast Healthcare Interoperability Resources (FHIR). We subsequently compared our Precision-DM with existing CDMs, including the National Cancer Institute's Genomic Data Commons (NCI GDC), mCODE, OSIRIS, the clinical Genome Data Model (cGDM), and the genomic CDM (gCDM). RESULTS: Precision-DM contained 16 profiles and 355 data elements. 39% of the elements derived values from selected terminologies or code sets, and 61% were mapped to FHIR. Although we used most elements contained in mCODE, we significantly expanded the profiles to include genomic annotations, resulting in a partial overlap of 50.7% between our core model and mCODE. Limited overlap was noted between Precision-DM and OSIRIS (33.2%), NCI GDC (21.4%), cGDM (9.3%), and gCDM (7.9%). Precision-DM covered most of the mCODE elements (87.7%), with less coverage for OSIRIS (35.8%), NCI GDC (11%), cGDM (26%) and gCDM (33.3%). CONCLUSION: Precision-DM supports clinical-genomic data standardization to support the MTB use case and may allow for harmonized data pulls across health care systems, academic institutions, and community medical centers. New paper led by @TaxiarchisB, @ValsamoA at @hopkinskimmel reports the development of Precision-DM, a #precision #oncology core data model that supports #clinical-#genomics data standardization and integration. [ABSTRACT FROM AUTHOR]

PURPOSE: Synoptic reporting provides a mechanism for uniform and structured pathology diagnostics. This paper demonstrates the functionality of Perl alternation and grouping expressions to classify electronic pathology reports generated from military treatment facilities. Eight Perl-based algorithms are validated to classify malignant melanoma, Hodgkin lymphoma, non-Hodgkin lymphoma, leukemia, and malignant neoplasms of the breast, ovary, testis, and thyroid. METHODS: Case finding cohorts were developed using diagnostic codes for neoplasm groups and matched by unique identifiers to obtain pathology records. Preprocessing techniques and Perl-based algorithms were applied to classify records as malignant, in situ, suspect, or nonapplicable, followed by a hand-review process to determine the accuracy of the algorithm classifications. Interrater reliability, sensitivity, specificity, positive predictive values, and negative predictive values were computed following abstractor adjudication. RESULTS: The specificity of the Perl-based algorithms was consistently high, over 98%. Very few benign results were classified as malignant or in situ by the Perl-based algorithms; the leukemia algorithm classification was the only group to demonstrate a positive predictive value below 95%, at 91.9%. Three algorithm classification groups demonstrated a sensitivity of < 80%, including malignant neoplasm of the ovary (33.3%), leukemia (52.8%), and non-Hodgkin lymphoma (62.9%). The pathology records for these results included substantial linguistic variation. CONCLUSION: This paper contextualizes the utility and value of an algorithm logic built around synoptic reporting to identify neoplasms from electronic pathology results. The major strength includes the application of Perl-based coding in SAS, an accessible software application, to develop highly specific algorithms across institutional variation in diagnostic documentation. [ABSTRACT FROM AUTHOR]

PURPOSE: We developed a system to automate analysis of the clinical oncology scientific literature from bibliographic databases and match articles to specific patient cohorts to answer specific questions regarding the efficacy of a treatment. The approach attempts to replicate a clinician's mental processes when reviewing published literature in the context of a patient case. We describe the system and evaluate its performance. METHODS: We developed separate ground truth data sets for each of the tasks described in the paper. The first ground truth was used to measure the natural language processing (NLP) accuracy from approximately 1,300 papers covering approximately 3,100 statements and approximately 25 concepts; performance was evaluated using a standard F1 score. The ground truth for the expert classifier model was generated by dividing papers cited in clinical guidelines into a training set and a test set in an 80:20 ratio, and performance was evaluated for accuracy, sensitivity, and specificity. RESULTS: The NLP models were able to identify individual attributes with a 0.7-0.9 F1 score, depending on the attribute of interest. The expert classifier machine learning model was able to classify the individual records with a 0.93 accuracy (95% CI, 0.9 to 0.96, P <.0001), and sensitivity and specificity of 0.95 and 0.91, respectively. Using a decision boundary of 0.5 for the positive (expert) label, the classifier demonstrated an F1 score of 0.92. CONCLUSION: The system identified and extracted evidence from the oncology literature with a high degree of accuracy, sensitivity, and specificity. This tool enables timely access to the most relevant biomedical literature, providing critical support to evidence-based practice in areas of rapidly evolving science. [ABSTRACT FROM AUTHOR]

PURPOSE Comprehensive health care centers are increasingly popular as they offer inclusive health care services under one roof. Often, these centers are formed by merging previously separate clinics. However, there is a lack of systematic guidance on the interprofessional, and interteam and intrateam dynamics that may develop during such an organizational change process. Using team process literature, we identify a possible model to explain how merging into a comprehensive cancer center (CCC) might influence health care teams and their subsequent outcomes, including patient experience. METHODS We used a mixed-method research design. Qualitative data were collected via semistructured interviews from 20 health care professionals employed at a recently merged CCC. During the time frame the interviews were collected, quantitative data were collected from 50 patients receiving treatment at the cancer center through anonymous paper-pencil surveys. Qualitative interviews were analyzed using thematic analysis, on the basis of the input-process-output team dynamics framework. Descriptive statistics were calculated for patient experience data. Trends between data collections were identified. RESULTS On the basis of our qualitative analysis, we provide an input-process-output framework that documents positive and negative aspects of interteam and intrateam dynamics associated with the merger process. Additionally, a number of connections were found between health care professional perceptions and quality patient experiences (eg, merger impacts on interteam and patient communication). CONCLUSION Our findings and model may assist in future merging efforts. Future CCCs may use the proposed framework to better understand and visualize their postmerger progress, in particular from the aspects of interprofessional, and interteam and intrateam dynamics. [ABSTRACT FROM AUTHOR]

PURPOSE: Accurate and efficient data collection is a challenge for quality improvement initiatives and clinical research. We describe the development of a custom electronic health record (EHR)–based registry to automatically extract structured Commission on Cancer axillary surgery-specific metrics from a custom synoptic note template included in the operative reports for patients with breast cancer undergoing surgery. METHODS: The smart functionality of our enterprise-based EHR system was leveraged to create a custom smart phrase to capture axillary surgery-specific variables. A multidisciplinary team developed structured data elements correlating to each axillary surgery-specific variable. These data elements were then included in a note template for the operative report. Each variable could be aggregated and converted into a single flat database through the EHR's reporting workbench and serve as a live, prospective registry for all users within the EHR. RESULTS: The final axillary surgery-specific note template in a synoptic format allowed for efficient and easy entry and automatic collection of breast cancer–specific metrics. From initial adoption in February 2021-December 2021, there were 1,254 patients who underwent breast surgery with axillary surgery. The operative notes allowed for automatic capture of metrics from 60.5% (n = 759) of patients. Data capture improved from 37.6% in the initial adoption period of 6 months to 86.2% in the last 5 months. CONCLUSION: We were able to demonstrate successful implementation of provider-driven structured data entry into EHR systems that permits automatic data capture. The end result is a custom synoptic note template and a real-time, prospective registry of breast cancer–specific Commission on Cancer metrics that are robust enough to use for quality improvement initiatives and clinical research. New @JCOCCI_ASCO paper on the implementation of a structured data entry system to collect axillary surgery specific metrics for #breast cancer patient demonstrates how existing #EHR systems can be used to improve documentation standards and surgical care. [ABSTRACT FROM AUTHOR]

PURPOSE: The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the literature to understand the clinical implications of pathogenic genetic variants. We developed and evaluated two machine learning models to classify abstracts as relevant to the penetrance—risk of cancer for germline mutation carriers—or prevalence of germline genetic mutations. MATERIALS AND METHODS: We conducted literature searches in PubMed and retrieved paper titles and abstracts to create an annotated data set for training and evaluating the two machine learning classification models. Our first model is a support vector machine (SVM) which learns a linear decision rule on the basis of the bag-of-ngrams representation of each title and abstract. Our second model is a convolutional neural network (CNN) which learns a complex nonlinear decision rule on the basis of the raw title and abstract. We evaluated the performance of the two models on the classification of papers as relevant to penetrance or prevalence. RESULTS: For penetrance classification, we annotated 3,740 paper titles and abstracts and evaluated the two models using 10-fold cross-validation. The SVM model achieved 88.93% accuracy—percentage of papers that were correctly classified—whereas the CNN model achieved 88.53% accuracy. For prevalence classification, we annotated 3,753 paper titles and abstracts. The SVM model achieved 88.92% accuracy and the CNN model achieved 88.52% accuracy. CONCLUSION: Our models achieve high accuracy in classifying abstracts as relevant to penetrance or prevalence. By facilitating literature review, this tool could help clinicians and researchers keep abreast of the burgeoning knowledge of gene–cancer associations and keep the knowledge bases for clinical decision support tools up to date. [ABSTRACT FROM AUTHOR]

PURPOSEKey to achieving better population-based outcomes for patients with lung cancer is the improvement of medical imaging and nuclear medicine infrastructure globally. This paper aims to outline why and spark relevant health systems strengthening.METHODSThe paper synthesizes the global lung cancer landscape, imaging referral guidelines (including resource-stratified ones), the reliance of TNM staging upon imaging, relevant multinational health technology assessments, and precisely how treatment selection and in turn patient outcomes hinge upon imaging findings. The final discussion presents data on current global gaps in both diagnostics (including imaging) and therapies and how, informed by such data, improved population-based outcomes are tangible through strategic planning.RESULTSImaging findings are central to appropriate lung cancer patient management and can variably lead to life-prolonging interventions and/or to life-enhancing palliative measures. Early-stage lung cancer can be treated with curative intent but, unfortunately, most patients with lung cancer still present at advanced stages and many patients lack access to both diagnostics and therapies. Furthermore, half of lung cancer cases occur in low- and middle-income countries. The role of medical imaging and nuclear medicine in lung cancer management, as outlined herein, may help inform strategic planning.CONCLUSIONLung cancer is the number one cancer killer worldwide. The essential role that medical imaging and nuclear medicine play in early diagnosis and disease staging cannot be overstated, pivotal in selecting the many patients for whom measurably improved outcomes are attainable. Prevention synergized with patient-centered, compassionate, high-quality lung cancer management provision mandate that strategic population-based planning, including universal health coverage strategies, should extend well beyond the scope of disease prevention to include both curative and noncurative treatment options for the millions afflicted with lung cancer.