Julia C Gage's research while affiliated with National Cancer Institute (USA) and other places

Background Cervical cancer is preventable with vaccination and early detection and treatment programs. However, for these programs to work as intended, stigma related to HPV and cervical cancer must be understood and addressed. We explored pre-existing stigma associated with HPV and cervical cancer in the public healthcare system and community of a low-resource setting prior to implementation of an HPV screen-and-treat program. Methods This study conducted thematic analysis of data collected during implementation of a novel HPV screen-and-treat system for cervical cancer early detection and treatment in Iquitos, Peru. We included 35 semi-structured interviews (19 health professionals, 16 women with cervical precancer or cancer), eight focus groups (70 community women), one workshop (14 health professionals), 210 counseling observations (with 20 nurse-midwives), and a document review. We used the Socio-Ecological Model to organize the analysis. Results We identified three main themes: 1. the implication that women are to blame for their HPV infection through characterizations of being easy or promiscuous, 2. the implication that men are to blame for women’s HPV infections through being considered careless or unfaithful, 3. HPV is shameful, embarrassing, and something that should be hidden from others. Consequently, in some cases, women refrained from getting screened for HPV. These themes were seen at the individual level among women, relationship level among women, men, and family members, community level among healthcare staff, and societal level within components of cervical cancer guidelines and male chauvinism. Conclusions Cervical cancer early detection and treatment programs in limited resource settings must address stigma entrenched throughout the entire healthcare system and community in order to sustainably and successfully implement and scale-up new programs. Interventions to tackle this stigma can incorporate messages about HPV infections and latency to lessen the focus on the influence of sexual behavior on HPV acquisition, and instead, promote screening and treatment as paramount preventative measures.

A number of challenges hinder artificial intelligence (AI) models from effective clinical translation. Foremost among these challenges are: (1) reproducibility or repeatability, which is defined as the ability of a model to make consistent predictions on repeat images from the same patient taken under identical conditions; (2) the presence of clinical uncertainty or the equivocal nature of certain pathologies, which needs to be acknowledged in order to effectively, accurately and meaningfully separate true normal from true disease cases; and (3) lack of portability or generalizability, which leads AI model performance to differ across axes of data heterogeneity. We recently investigated the development of an AI pipeline on digital images of the cervix, utilizing a multi-heterogeneous dataset (“SEED”) of 9,462 women (17,013 images) and a multi-stage model selection and optimization approach, to generate a diagnostic classifier able to classify images of the cervix into “normal”, “indeterminate” and “precancer/cancer” (denoted as “precancer+”) categories. In this work, we investigated the performance of this multiclass classifier on external data (“EXT”) not utilized in training and internal validation, to assess the portability of the classifier when moving to new settings. We assessed both the repeatability and classification performance of our classifier across the two axes of heterogeneity present in our dataset: image capture device and geography, utilizing both out-of-the-box inference and retraining with “EXT”. Our results indicate strong repeatability of our multiclass model utilizing Monte-Carlo (MC) dropout, which carries over well to “EXT” (95% limit of agreement range = 0.2 - 0.4) even in the absence of retraining, as well as strong classification performance of our model on “EXT” that is achieved with retraining (% extreme misclassifications = 4.0% for n = 26 “EXT” individuals added to “SEED” in a 2n normal : 2n indeterminate : n precancer+ ratio), and incremental improvement of performance following retraining with images from additional individuals. We additionally find that device-level heterogeneity affects our model performance more than geography-level heterogeneity. Our work supports both (1) the development of comprehensively designed AI pipelines, with design strategies incorporating multiclass ground truth and MC dropout, on multi-heterogeneous data that are specifically optimized to improve repeatability, accuracy, and risk stratification; and (2) the need for optimized retraining approaches that address data heterogeneity (e.g., when moving to a new device) to facilitate effective use of AI models in new settings. AUTHOR SUMMARY Artificial intelligence (AI) model robustness has emerged as a pressing issue, particularly in medicine, where model deployment requires rigorous standards of approval. In the context of this work, model robustness refers to both the reproducibility of model predictions across repeat images, as well as the portability of model performance to external data. Real world clinical data is often heterogeneous across multiple axes, with distribution shifts in one or more of these axes often being the norm. Current deep learning (DL) models for cervical cancer and in other domains exhibit poor repeatability and overfitting, and frequently fail when evaluated on external data. As recently as March 2023, the FDA issued a draft guidance on effective implementation of AI/DL models, proposing the need for adapting models to data distribution shifts. To surmount known concerns, we conducted a thorough investigation of the generalizability of a deep learning model for cervical cancer screening, utilizing the distribution shifts present in our large, multi-heterogenous dataset. We highlight optimized strategies to adapt an AI-based clinical test, which in our case was a cervical cancer screening triage test, to external data from a new setting. Given the severe clinical burden of cervical cancer, and the fact that existing screening approaches, such as visual inspection with acetic acid (VIA), are unreliable, inaccurate, and invasive, there is a critical need for an automated, AI-based pipeline that can more consistently evaluate cervical lesions in a minimally invasive fashion. Our work represents one of the first efforts at generating and externally validating a cervical cancer diagnostic classifier that is reliable, consistent, accurate, and clinically translatable, in order to triage women into appropriate risk categories.

Background Cervical cancer is preventable with vaccination and early detection and treatment programs. However, in order for these programs to work as intended, stigma related to HPV and cervical cancer must be understood and addressed. We explored pre-existing stigma associated with HPV and cervical cancer in the public healthcare system of a low-resource setting prior to implementation of an HPV screen-and-treat program. Methods This study conducted thematic analysis of data collected during implementation of a novel HPV screen-and-treat system for cervical cancer early detection and treatment in Iquitos, Peru. We included 35 semi-structured interviews (19 health professionals, 16 women with cervical precancer or cancer), eight focus groups (70 community women), one workshop (14 health professionals), 210 counseling observations (with 20 nurse-midwives), and a document review. We used the Socio-Ecological Model to organize the analysis. Results We identified three main themes: 1. the implication that women are to blame for their HPV infection through characterizations of being easy or promiscuous, 2. the implication that men are to blame for women’s HPV infections through being considered careless or unfaithful, 3. HPV is shameful, embarrassing, and something that should be hidden from others. Consequently, in some cases, women refrained from getting screened for HPV. These themes were seen at the individual level among women, relationship level among women, men, and family members, community level among healthcare staff, and societal level within components of cervical cancer guidelines and male chauvinism. Conclusions Cervical cancer early detection and treatment programs in limited resource settings must address stigma entrenched throughout the entire healthcare system in order to sustainably and successfully implement and scale-up new programs. Interventions to tackle this stigma can incorporate messages about HPV infections and latency to lessen the focus on the influence of sexual behavior on HPV acquisition, and instead, promote screening and treatment as paramount preventative measures.

Purpose: In many countries, implementation planning for delivery of cancer screening services functions as a ‘top-down’ process, often resulting in fragmentation and bottlenecks at points of service delivery. Participatory engagement of health system planners and actors from across cancer screening and treatment continuum involved with implementation, planning, and adaptation is hypothesized to lead to plans that have a higher likelihood of adoption and sustainability. We tested the feasibility of conducting a 4-day series of participatory ‘design workshops’ for implementation of the recently initiated HPV screening program in the DIRIS Lima Norte (DLN) region of Peru. Methods: The workshop agendas were co-designed by the Peruvian Ministry of Health (MINSA) and the National Cancer Institute (NCI) using principles of participatory action research, implementation science, and systems thinking. The workshop objectives were to clarify the goals and processes of the HPV cervical screening program and reflect on the initial implementation experience. Workshop design was attentive to a) building trust among the health system planners and actors, b) surfacing misconceptions and process bottlenecks, c) equitable representation of perspectives on the process from all levels of the screening system, and d) shared decision-making in actions to improve the system. Results: Through real-time participatory reflection and process mapping of the screening program, context-specific challenges were rapidly identified. The process maps helped participants gain a shared understanding of the complexity of the screening system and quickly identified how one part of the system can create barriers for proximal and distal parts of the system. Participants mentioned feeling detached from the distal barriers before the workshops but now understood their role in the decision-making and problem-solving processes and demonstrated a willingness to work with the regional director to implement process improvements in the system, specifically to ensure women testing positive received the appropriate follow-up care. Conclusion: Rapid embedded implementation research using facilitated workshops with broad health system representation to reflect on the processes and procedures was an acceptable quality improvement activity. MINSA plans to replicate this experience in other regions and to continue to create a culture of trust and establishment of learning health systems. Citation Format: Fatou Jallow, Andrea Matos Orbegozo, Maria Del Carmen Caruhapoma, Víctor A. Palacios, Milagros Montes, Carlos Santos, Margarita Correa-Mendez, Aubrey Villalobos, Alejandro Salicrup, Jose Jeronimo, Laura Nervi, Patti Gravitt, Julia Gage. Design Workshops: Participatory Co-Design and Iterative Adaptation of Cervical Cancer Screening Implementation Plans in Peru [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 28.

https://ipvconference.org/abstract-e-book/

Cervical cancer screening and management in the U.S. has adopted a risk-based approach. However, the majority of cervical cancer cases and deaths occur in resource-limited settings, where screening and management are not widely available. We describe a conceptual model that optimizes cervical cancer screening and management in resource-limited settings by utilizing a risk-based approach. The principles of risk-based screening and management in resource limited settings include (1) ensure that the screening method effectively separates low-risk from high-risk patients; (2) directing resources to populations at the highest cancer risk; (3) screen using HPV testing via self-sampling; (4) utilize HPV genotyping to improve risk stratification and better determine who will benefit from treatment, and (5) automated visual evaluation with artificial intelligence may further improve risk stratification. Risk-based screening and management in resource limited settings can optimize prevention by focusing triage and treatment resources on the highest risk patients while minimizing interventions in lower risk patients.

Background: High-risk human papillomavirus (hrHPV) may cause more than 99% of cervical cancers worldwide. Little is known about performance differences in tests for hrHPV. Objective: This study analysed agreement for detection of hrHPV between the established, clinically validated Xpert HPV assay and the novel isothermal amplification-based AmpFire HPV genotyping assay. Methods: This study was nested in a larger project on cervical cancer screening among approximately 5000 women living with HIV in Kigali, Rwanda. This sub-study included 298 participants who underwent initial screening for cervical cancer using the Xpert HPV assay and visual inspection with acetic acid in 2017 and tested positive by either or both. Participants were rescreened using colposcopy, and cervical samples were collected between June 2018 and June 2019. Samples were then tested for HPV using the Xpert HPV assay and AmpFire HPV genotyping assay. Agreement between results from both tests was analysed using an exact version of McNemar test and chi-square test. Results: Overall agreement and kappa value for detection of hrHPV by Xpert and AmpFire were 89% and 0.77 (95% confidence interval: 0.70–0.85). AmpFire was marginally more likely to diagnose hrHPV-positive than Xpert (p = 0.05), due primarily to the extra positivity for HPV16 (p 0.001). Conclusion: Overall, there was good to excellent agreement between the Xpert and AmpFire when testing hrHPV types among women living with HIV. AmpFire was more likely to test extra cases of HPV16, the most carcinogenic HPV type, but the clinical meaning of detecting additional HPV16 infections remains unknown.

Introduction Prophylactic human papillomavirus (HPV) vaccines have been shown to be highly effective in protecting women against cervical infections, high-grade abnormalities and cancer caused by the targeted HPV types. However, the evidence for their effectiveness in women living with HIV (WLWH) is less clear. Methods WLWH and HIV-negative women who likely did (birth cohorts 1996 and later) and WLWH and HIV(−) negative who likely did not (birth cohorts before 1996) receive HPV vaccination (n=3028; 757 participants for each of the four groups). Between groups, we will compare cervicovaginal, anal and oral prevalent and 6–12 month persistent HPV6/11/16/18 infections as measured using a modified AmpFire HPV genotyping assay that tests for 15 high-risk or intermediate-risk HPV genotypes, HPV6 and HPV11. We will also compare the HPV immune response in HPV-vaccinated WLWH to HPV-vaccinated HIV-negative women using an anti-HPV16 and anti-HPV18 ELISA. Vaccination status will be confirmed through national vaccination records. Analysis We will calculate point prevalence and prevalence of 6–12 month persisting infections by individual HPV-type specific infections and groups of infections for each anatomic site and for each group of women. Results will be stratified by age at vaccination, age at enrolment and the number of doses (3 vs 2) as well as other factors possibly associated with HPV prevalence. Differences in endpoints between groups, overall and between subgroups, will be tested for statistical significance (p<0.05) using Fisher’s exact or Pearson χ ² test. Differences in geometric mean titres and seropositivity will be tested for statistical significance using the Mann-Whitney and Fisher’s exact tests, respectively. Ethics and dissemination The study was approved by the Albert Einstein College of Medicine Institutional Review Board and the Rwanda National Ethics Committee. Results will be disseminated through publication in peer-reviewed journals.

Accelerated cervical cancer control will require widespread human papillomavirus (HPV) vaccination and screening. For screening, sensitive HPV testing with an option of self‐collection is increasingly desirable. HPV typing predicts risk of precancer/cancer, which could be useful in management, but most current typing assays are expensive and/or complicated. An existing 15‐type isothermal amplification assay (AmpFire, Atila Biosystems, USA) was redesigned as a 13‐type assay (ScreenFire) for public health use. The redesigned assay groups HPV types into four channels with differential cervical cancer risk: (a) HPV16, (b) HPV18/45, (c) HPV31/33/35/52/58 and (d) HPV39/51/56/59/68. Since the assay will be most useful in resource‐limited settings, we chose a stratified random sample of 453 provider‐collected samples from a population‐based screening study in rural Nigeria that had been initially tested with MY09‐MY11‐based PCR with oligonucleotide hybridization genotyping. Frozen residual specimens were masked and retested at Atila Biosystems. Agreement on positivity between ScreenFire and prior PCR testing was very high for each of the channels. When we simulated intended use, that is, a hierarchical result in order of clinical importance of the type groups (HPV16 > 18/45 > 31/33/35/52/58 > 39/51/56/59/68), the weighted kappa for ScreenFire vs PCR was 0.90 (95% CI: 0.86‐0.93). The ScreenFire assay is mobile, relatively simple, rapid (results within 20‐60 minutes) and agrees well with reference testing particularly for the HPV types of greatest carcinogenic risk. If confirmed, ScreenFire or similar isothermal amplification assays could be useful as part of risk‐based screening and management.