Faculty Bibliography

Objective: We sought to prospectively evaluate the feasibility of obtaining genetic testing for at least 1 first- or second-degree family member of a proband known to have actionable germline mutation associated with endometrial and/or ovarian cancer through a coordinated referral system. We also identified barriers to genetic assessment in family members. Here we report initial probands screened and their reasons for declining cascade testing.
Method(s): Patients with a diagnosed pathogenic or suspected pathogenic mutation associated with ovarian and/or endometrial cancer were identified from the gynecologic oncology and genetics clinics. If patients did not consent to the study, their reasons for declining participation were documented. Patients who provided consent were asked to contact their first- and/or second-degree relatives to disclose their genetic testing results and advise them to contact our center for a referral to a genetic counselor. The number of relatives per proband who contacted us for a genetic counseling referral was recorded. In addition to providing the referral, we followed up with relatives to determine whether they attended their genetic counseling appointment, received genetic testing, or took any cancer risk-reducing measures based on their results.
Result(s): This study opened in March 2019. To date, we have screened 71 patients and enrolled 26 (37%). Among the 45 patients who were screened but not enrolled, 48.9% (n = 22) reported that their reason for declining participation in the study was that their family members had already received genetic testing. Other common reasons for declining participation were family members refusing testing (17.8%, n = 8) or no eligible family members (17.8%, n = 8) (Table 1).
Conclusion(s): The majority of probands declined participation in this facilitated cascade testing protocol. The most common reason for lack of participation was family members already having genetic testing or not having eligible family members. Patients who declined participation because family members refused testing could benefit from counseling on how to best to communicate with their relatives. Genetic testing for both patients and their relatives is critical to provision of appropriate cancer screening and prevention services. Knowledge of these barriers is important to further improve cascade testing among family members.
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Automated Visual Examination (AVE) is a deep learning algorithm that aims to improve the effectiveness of cervical precancer screening, particularly in low- and medium-resource regions. It was trained on data from a large longitudinal study conducted by the National Cancer Institute (NCI) and has been shown to accurately identify cervices with early stages of cervical neoplasia for clinical evaluation and treatment. The algorithm processes images of the uterine cervix taken with a digital camera and alerts the user if the woman is a candidate for further evaluation. This requires that the algorithm be presented with images of the cervix, which is the object of interest, of acceptable quality, i.e., in sharp focus, with good illumination, without shadows or other occlusions, and showing the entire squamo-columnar transformation zone. Our prior work has addressed some of these constraints to help discard images that do not meet these criteria. In this work, we present a novel algorithm that determines that the image contains the cervix to a sufficient extent. Non-cervix or other inadequate images could lead to suboptimal or wrong results. Manual removal of such images is labor intensive and time-consuming, particularly in working with large retrospective collections acquired with inadequate quality control. In this work, we present a novel ensemble deep learning method to identify cervix images and non-cervix images in a smartphone-acquired cervical image dataset. The ensemble method combined the assessment of three deep learning architectures, RetinaNet, Deep SVDD, and a customized CNN (Convolutional Neural Network), each using a different strategy to arrive at its decision, i.e., object detection, one-class classification, and binary classification. We examined the performance of each individual architecture and an ensemble of all three architectures. An average accuracy and F-1 score of 91.6% and 0.890, respectively, were achieved on a separate test dataset consisting of more than 30,000 smartphone-captured images.

PURPOSE/OBJECTIVE:Until human papillomavirus (HPV)-based cervical screening is more affordable and widely available, visual inspection with acetic acid (VIA) is recommended by the WHO for screening in lower-resource settings. Visual inspection will still be required to assess the cervix for women whose screening is positive for high-risk HPV. However, the quality of VIA can vary widely, and it is difficult to maintain a well-trained cadre of providers. We developed a smartphone-enhanced VIA platform (SEVIA) for real-time secure sharing of cervical images for remote supportive supervision, data monitoring, and evaluation. METHODS:We assessed programmatic outcomes so that findings could be translated into routine care in the Tanzania National Cervical Cancer Prevention Program. We compared VIA positivity rates (for HIV-positive and HIV-negative women) before and after implementation. We collected demographic, diagnostic, treatment, and loss-to-follow-up data. RESULTS:From July 2016 to June 2017, 10,545 women were screened using SEVIA at 24 health facilities across 5 regions of Tanzania. In the first 6 months of implementation, screening quality increased significantly from the baseline rate in the prior year, with a well-trained cadre of more than 50 health providers who "graduated" from the supportive-supervision training model. However, losses to follow-up for women referred for further evaluation or to a higher level of care were considerable. CONCLUSION/CONCLUSIONS:The SEVIA platform is a feasible, quality improvement, mobile health intervention that can be integrated into a national cervical screening program. Our model demonstrates potential for scalability. As HPV screening becomes more affordable, the platform can be used for visual assessment of the cervix to determine amenability for same-day ablative therapy and/or as a secondary triage step, if needed.

BACKGROUND:Breast cancer is the most common cancer among women in India. Jhpiego, a not-for-profit health organization, is providing technical assistance for developing an evidence-based model of breast health care in the states of Uttar Pradesh and Jharkhand in India. METHODS:A situational assessment of breast health care services using validated tools was conducted in the 2 states. RESULTS:Findings of the assessment were presented to the Breast Health Technical Advisory Committee comprised of subject experts and government functionaries. The committee, guided by Breast Health Global Initiative resource-stratified guidelines, developed a conceptual framework for integration of breast health services into the existing health system. This conceptual framework was presented to the Technical Advisory Groups (TAGs) of the respective state governments. Each TAG then developed an operationally feasible, contextually appropriate implementation plan in alignment with the national guidelines for noncommunicable diseases. This implementation plan guided the rollout of the breast health care program in the Lucknow (Uttar Pradesh) and Ranchi (Jharkhand) districts. CONCLUSIONS:Early results from the implementation suggest that it is feasible to integrate the breast health care pathway with the ongoing National Cancer Control Program of India.

BACKGROUND:The Breast Health Global Initiative (BHGI) established a series of resource-stratified, evidence-based guidelines to address breast cancer control in the context of available resources. Here, the authors describe methodologies and health system prerequisites to support the translation and implementation of these guidelines into practice. METHODS:In October 2018, the BHGI convened the Sixth Global Summit on Improving Breast Healthcare Through Resource-Stratified Phased Implementation. The purpose of the summit was to define a stepwise methodology (phased implementation) for guiding the translation of resource-appropriate breast cancer control guidelines into real-world practice. Three expert consensus panels developed stepwise, resource-appropriate recommendations for implementing these guidelines in low-income and middle-income countries as well as underserved communities in high-income countries. Each panel focused on 1 of 3 specific aspects of breast cancer care: 1) early detection, 2) treatment, and 3) health system strengthening. RESULTS:Key findings from the summit and subsequent article preparation included the identification of phased-implementation prerequisites that were explored during consensus debates. These core issues and concepts are key components for implementing breast health care that consider real-world resource constraints. Communication and engagement across all levels of care is vital to any effectively operating health care system, including effective communication with ministries of health and of finance, to demonstrate needs, outcomes, and cost benefits. CONCLUSIONS:Underserved communities at all economic levels require effective strategies to deploy scarce resources to ensure access to timely, effective, and affordable health care. Systematically strategic approaches translating guidelines into practice are needed to build health system capacity to meet the current and anticipated global breast cancer burden.

When breast cancer is detected and treated early, the chances of survival are very high. However, women in many settings face complex barriers to early detection, including social, economic, geographic, and other interrelated factors, which can limit their access to timely, affordable, and effective breast health care services. Previously, the Breast Health Global Initiative (BHGI) developed resource-stratified guidelines for the early detection and diagnosis of breast cancer. In this consensus article from the sixth BHGI Global Summit held in October 2018, the authors describe phases of early detection program development, beginning with management strategies required for the diagnosis of clinically detectable disease based on awareness education and technical training, history and physical examination, and accurate tissue diagnosis. The core issues address include finance and governance, which pertain to successful planning, implementation, and the iterative process of program improvement and are needed for a breast cancer early detection program to succeed in any resource setting. Examples are presented of implementation, process, and clinical outcome metrics that assist in program implementation monitoring. Country case examples are presented to highlight the challenges and opportunities of implementing successful breast cancer early detection programs, and the complex interplay of barriers and facilitators to achieving early detection for breast cancer in real-world settings are considered.

BACKGROUND:Breast cancer is the leading cause of female mortality in low-income and middle-income countries (LMICs). Early detection of breast cancer, either through screening or early diagnosis initiatives, led by community health workers (CHWs) has been proposed as a potential way to address the unjustly high mortality rates. We therefore document: (1) where and how CHWs are currently deployed in this role; (2) how CHWs are trained, including the content, duration and outcomes of training; and (3) the evidence on costs associated with deploying CHWs in breast cancer early detection. METHODS:We conducted a systematic scoping review and searched eight major databases, as well as the grey literature. We included original studies focusing on the role of CHWs to assist in breast cancer early detection in a country defined as a LMIC according to the World Bank. FINDINGS/RESULTS:16 eligible studies were identified. Several roles were identified for CHWs including awareness raising and community education (n=13); history taking (n=7); performing clinical breast examination (n=9); making onward referrals (n=7); and assisting in patient navigation and follow-up (n=4). Details surrounding training programmes were poorly reported and no studies provided a formal cost analysis. CONCLUSIONS:Despite the relative paucity of studies addressing the role of CHWs in breast cancer early detection, as well as the heterogeneity of existing studies, evidence suggests that CHWs can play a number of important roles in breast cancer early detection initiatives in LMICs. However, if they are to realise their full potential, they must be appropriately supported within the wider health system.