RESUMO
Accurate survival estimates are needed for guiding cancer control efforts in sub-Saharan Africa, but previous studies have been hampered by unknown biases due to excessive loss to follow-up (LTFU). In the African Breast Cancer-Disparities in Outcomes Study, a prospective breast cancer cohort study, we implemented active mobile health follow-up, telephoning each woman or her next-of-kin (NOK) trimonthly on her mobile phone to update information on her vital status. Dates of every contact with women/NOK were analyzed from diagnosis in 2014-2017 to the earliest of September 1, 2018, death, or 3 years postdiagnosis. The cumulative incidence of being LTFU was calculated considering deaths as competing events. In all, 1,490 women were followed for a median of 24.2 (interquartile range (IQR), 14.2-34.5) months, corresponding to 8,529 successful contacts (77% of total contacts) with the women/NOK. Median time between successful contacts was 3.0 (IQR, 3.0-3.7) months. In all, 71 women (5.3%) were LTFU at 3 years: 0.8% in Nigeria, 2.2% in Namibia, and 5.6% in Uganda. Because of temporary discontinuity of active follow-up, 20.3% of women were LTFU after 2 years in Zambia. The median time to study notification of a death was 9.1 (IQR, 3.9-14.0) weeks. Although the present study was not a randomized controlled trial, in this cancer cohort with active mobile health follow-up, LTFU was much lower than in previous studies and enabled estimation of up-to-date and reliable cancer survival.
Assuntos
Neoplasias da Mama/epidemiologia , Sobreviventes de Câncer/estatística & dados numéricos , Perda de Seguimento , Telemedicina/estatística & dados numéricos , Adulto , África Subsaariana/epidemiologia , Idoso , Feminino , Seguimentos , Humanos , Pessoa de Meia-Idade , Estudos ProspectivosRESUMO
INTRODUCTION: Efficient NTDs elimination strategies require effective surveillance and targeted interventions. Traditional methods are costly and time-consuming, often failing to cover entire populations in case of movement restrictions. To address these challenges, a morbidity image-based surveillance system is being developed. This innovative approach which leverages the smartphone technology aims at simultaneous surveillance of multiple NTDs, enhancing cost-efficiency, reliability, and community involvement, particularly in areas with movement constraints. Moreover, it holds promise for post-elimination surveillance. METHODOLOGY: The pilot of this method will be conducted across three states in southern Nigeria. It will target people affected by Neglected Tropical Diseases and members of their communities. The new surveillance method will be introduced to target communities in the selected states through community stakeholder's advocacy meetings and awareness campaigns. The pilot which is set to span eighteen months, entails sensitizing NTDs-affected individuals and community members using signposts, posters, and handbills, to capture photos of NTDs manifestations upon notice using smartphones. These images, along with pertinent demographic information, will be transmitted to a dedicated server through WhatsApp or Telegram accounts. The received images will be reviewed and organized at backend and then forwarded to a panel of experts for identification and annotation to specific NTDs. Data generated, along with geocoordinate information, will be used to create NTDs morbidity hotspot maps using ArcGIS. Accompanying metadata will be used to generate geographic and demographic distributions of various NTDs identified. To protect privacy, people will be encouraged to send manifestation photos of the affected body part only without any identifiable features. EVALUATION PROTOCOL: NTDs prevalence data obtained using conventional surveillance methods from both the pilot and selected control states during the pilot period will be compared with data from the CIMS-NTDs method to determine its effectiveness. EXPECTED RESULTS AND CONCLUSION: It is expected that an effective, privacy-conscious, population inclusive new method for NTDs surveillance, with the potential to yield real-time data for the identification of morbidity hotspots and distribution patterns of NTDs will be established. The results will provide insights into the effectiveness of the new surveillance method in comparison to traditional approaches, potentially advancing NTDs elimination strategies.