Pharmacovigilance programmes monitor and help ensuring the safe use of medicines which is critical to the success of public health programmes. The commonest method used for discovering previously ...unknown safety risks is spontaneous notifications. In this study we examine the use of data mining algorithms to identify signals from adverse events reported in a phase IIIb/IV clinical trial evaluating the efficacy and safety of several Artemisinin-based combination therapies (ACTs) for treatment of uncomplicated malaria in African children.
We used paediatric safety data from a multi-site, multi-country clinical study conducted in seven African countries (Burkina Faso, Gabon, Nigeria, Rwanda, Uganda, Zambia, and Mozambique). Each site compared three out of four ACTs, namely amodiaquine-artesunate (ASAQ), dihydroartemisinin-piperaquine (DHAPQ), artemether-lumefantrine (AL) or chlorproguanil/dapsone and artesunate (CD+A). We examine two pharmacovigilance signal detection methods, namely proportional reporting ratio and Bayesian Confidence Propagation Neural Network on the clinical safety dataset.
Among the 4,116 children (6-59 months old) enrolled and followed up for 28 days post treatment, a total of 6,238 adverse events were reported resulting into 346 drug-event combinations. Nine signals were generated both by proportional reporting ratio and Bayesian Confidence Propagation Neural Network. A review of the manufacturer package leaflets, an online Multi-Drug Symptom/Interaction Checker (DoubleCheckMD) and further by therapeutic area experts reduced the number of signals to five. The ranking of some drug-adverse reaction pairs on the basis of their signal index differed between the two methods.
Our two data mining methods were equally able to generate suspected signals using the pooled safety data from a phase IIIb/IV clinical trial. This analysis demonstrated the possibility of utilising clinical studies safety data for key pharmacovigilance activities like signal detection and evaluation. This approach can be applied to complement the spontaneous reporting systems which are limited by under reporting.
Drug prescription practices depend on several factors related to the patient, health worker and health facilities. A better understanding of the factors influencing prescription patterns is essential ...to develop strategies to mitigate the negative consequences associated with poor practices in both the public and private sectors.
A cross-sectional study was conducted in rural Tanzania among patients attending health facilities, and health workers. Patients, health workers and health facilities-related factors with the potential to influence drug prescription patterns were used to build a model of key predictors. Standard data mining methodology of classification tree analysis was used to define the importance of the different factors on prescription patterns.
This analysis included 1,470 patients and 71 health workers practicing in 30 health facilities. Patients were mostly treated in dispensaries. Twenty two variables were used to construct two classification tree models: one for polypharmacy (prescription of ≥3 drugs) on a single clinic visit and one for co-prescription of artemether-lumefantrine (AL) with antibiotics. The most important predictor of polypharmacy was the diagnosis of several illnesses. Polypharmacy was also associated with little or no supervision of the health workers, administration of AL and private facilities. Co-prescription of AL with antibiotics was more frequent in children under five years of age and the other important predictors were transmission season, mode of diagnosis and the location of the health facility.
Standard data mining methodology is an easy-to-implement analytical approach that can be useful for decision-making. Polypharmacy is mainly due to the diagnosis of multiple illnesses.
Under-five and maternal mortality were halved in the Millennium Development Goals (MDG) era, with slower reductions for 2.6 million neonatal deaths and 2.6 million stillbirths. The Every Newborn ...Action Plan aims to accelerate progress towards national targets, and includes an ambitious Measurement Improvement Roadmap. Population-based household surveys, notably Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys, are major sources of population-level data on child mortality in countries with weaker civil registration and vital statistics systems, where over two-thirds of global child deaths occur. To estimate neonatal/child mortality and pregnancy outcomes (stillbirths, miscarriages, birthweight, gestational age) the most common direct methods are: (1) the standard DHS-7 with Full Birth History with additional questions on pregnancy losses in the past 5 years (FBH
) or (2) a Full Pregnancy History (FPH). No direct comparison of these two methods has been undertaken, although descriptive analyses suggest that the FBH
may underestimate mortality rates particularly for stillbirths.
This is the protocol paper for the Every Newborn-INDEPTH study (INDEPTH Network, International Network for the Demographic Evaluation of Populations and their Health Every Newborn, Every Newborn Action Plan), aiming to undertake a randomised comparison of FBH
and FPH to measure pregnancy outcomes in a household survey in five selected INDEPTH Network sites in Africa and South Asia (Bandim in urban and rural Guinea-Bissau; Dabat in Ethiopia; IgangaMayuge in Uganda; Kintampo in Ghana; Matlab in Bangladesh). The survey will reach >68 000 pregnancies to assess if there is ≥15% difference in stillbirth rates. Additional questions will capture birthweight, gestational age, birth/death certification, termination of pregnancy and fertility intentions. The World Bank's Survey Solutions platform will be tailored for data collection, including recording paradata to evaluate timing. A mixed methods assessment of barriers and enablers to reporting of pregnancy and adverse pregnancy outcomes will be undertaken.
This large-scale study is the first randomised comparison of these two methods to capture pregnancy outcomes. Results are expected to inform the evidence base for survey methodology, especially in DHS, regarding capture of stillbirths and other outcomes, notably neonatal deaths, abortions (spontaneous and induced), birthweight and gestational age. In addition, this study will inform strategies to improve health and demographic surveillance capture of neonatal/child mortality and pregnancy outcomes.
An estimated 5·1 million stillbirths and neonatal deaths occur annually. Household surveys, most notably the Demographic and Health Survey (DHS), run in more than 90 countries and are the main data ...source from the highest burden regions, but data-quality concerns remain. We aimed to compare two questionnaires: a full birth history module with additional questions on pregnancy losses (FBH+; the current DHS standard) and a full pregnancy history module (FPH), which collects information on all livebirths, stillbirths, miscarriages, and neonatal deaths.
Women residing in five Health and Demographic Surveillance System sites within the INDEPTH Network (Bandim in Guinea-Bissau, Dabat in Ethiopia, IgangaMayuge in Uganda, Matlab in Bangladesh, and Kintampo in Ghana) were randomly assigned (individually) to be interviewed using either FBH+ or FPH between July 28, 2017, and Aug 13, 2018. The primary outcomes were stillbirths and neonatal deaths in the 5 years before the survey interview (measured by stillbirth rate SBR and neonatal mortality rate NMR) and mean time taken to complete the maternity history section of the questionnaire. We also assessed between-site heterogeneity. This study is registered with the Research Registry, 4720.
69 176 women were allocated to be interviewed by either FBH+ (n=34 805) or FPH (n=34 371). The mean time taken to complete FPH (10·5 min) was longer than for FBH+ (9·1 min; p<0·0001). Using FPH, the estimated SBR was 17·4 per 1000 total births, 21% (95% CI −10 to 62) higher than with FBH+ (15·2 per 1000 total births; p=0·20) in the 5 years preceding the survey interview. There was strong evidence of between-site heterogeneity (I2=80·9%; p<0·0001), with SBR higher for FPH than for FBH+ in four of five sites. The estimated NMR did not differ between modules (FPH 25·1 per 1000 livebirths vs FBH+ 25·4 per 1000 livebirths), with no evidence of between-site heterogeneity (I2=0·7%; p=0·40).
FPH takes an average of 1·4 min longer to complete than does FBH+, but has the potential to increase reporting of stillbirths in high burden contexts. The between-site heterogeneity we found might reflect variations in interviewer training and survey implementation, emphasising the importance of interviewer skills, training, and consistent implementation in data quality.
Children's Investment Fund Foundation.
Background Pharmacovigilance programmes monitor and help ensuring the safe use of medicines which is critical to the success of public health programmes. The commonest method used for discovering ...previously unknown safety risks is spontaneous notifications. In this study we examine the use of data mining algorithms to identify signals from adverse events reported in a phase IIIb/IV clinical trial evaluating the efficacy and safety of several Artemisinin-based combination therapies (ACTs) for treatment of uncomplicated malaria in African children. Methods We used paediatric safety data from a multi-site, multi-country clinical study conducted in seven African countries (Burkina Faso, Gabon, Nigeria, Rwanda, Uganda, Zambia, and Mozambique). Each site compared three out of four ACTs, namely amodiaquine-artesunate (ASAQ), dihydroartemisinin-piperaquine (DHAPQ), artemether-lumefantrine (AL) or chlorproguanil/dapsone and artesunate (CD+A). We examine two pharmacovigilance signal detection methods, namely proportional reporting ratio and Bayesian Confidence Propagation Neural Network on the clinical safety dataset. Results Among the 4,116 children (6-59 months old) enrolled and followed up for 28 days post treatment, a total of 6,238 adverse events were reported resulting into 346 drug-event combinations. Nine signals were generated both by proportional reporting ratio and Bayesian Confidence Propagation Neural Network. A review of the manufacturer package leaflets, an online Multi-Drug Symptom/Interaction Checker (DoubleCheckMD) and further by therapeutic area experts reduced the number of signals to five. The ranking of some drug-adverse reaction pairs on the basis of their signal index differed between the two methods. Conclusions Our two data mining methods were equally able to generate suspected signals using the pooled safety data from a phase IIIb/IV clinical trial. This analysis demonstrated the possibility of utilising clinical studies safety data for key pharmacovigilance activities like signal detection and evaluation. This approach can be applied to complement the spontaneous reporting systems which are limited by under reporting.
Global mortality estimates remain heavily dependent on household surveys in low- and middle-income countries, where most under-five deaths occur. Few studies have assessed the accuracy of mortality ...data or determinants of capturing births in surveys.
The Every Newborn-INDEPTH study (EN-INDEPTH) included a large, multi-country survey of women aged 15-49 interviewed about livebirths and their survival status in five Health and Demographic Surveillance Systems (HDSSs). The HDSSs undertake regular household visits to register births and deaths for a given population. We analysed EN-INDEPTH survey data to assess background factors associated with not recalling a complete date-of-birth. We calculated Kaplan-Meier survival estimates for both survey and HDSS data and describe age-at-death distributions during the past 5 years for children born to the same women. We assessed the proportion of HDSS-births that could be matched on month-of-birth to survey-births and used regression models to identify factors associated with matching.
69,176 women interviewed in the survey reported 109,817 births and 3064 deaths in children under 5 years in the 5 years prior to the survey. In the HDSS data, the same women had 83,768 registered births and 2335 under-five deaths in the same period. A complete date-of-birth was not reported for 1-7% of survey-births. Birthdates were less likely to be complete for dead children and children born to women of higher parity or with little/no education. Distributions of reported age-at-death indicated heaping at full weeks (neonatal period) and at 12 months. Heaping was more pronounced in the survey data. Survey estimates of under-five mortality rates were similar to HDSS estimates of under-five mortality in two of five sites, higher in the survey in two sites (15%, 41%) and lower (24%) in one site. The proportion of HDSS-births matched to survey-births ranged from 51 to 89% across HDSSs and births of children who had died were less likely to be matched.
Mortality estimates in the survey and HDSS were not markedly different for most sites. However, neither source is a "gold standard" and both sources miss some events. Research is required to improve capture and accuracy to better track newborn and child survival targets.
An estimated 40% of pregnancies globally are unintended. Measurement of pregnancy intention in low- and middle-income countries relies heavily on surveys, notably Demographic and Health Surveys ...(DHS), yet few studies have evaluated survey questions. We examined questions for measuring pregnancy intention, which are already in the DHS, and additional questions and investigated associations with maternity care utilisation and adverse pregnancy outcomes.
The EN-INDEPTH study surveyed 69,176 women of reproductive age in five Health and Demographic Surveillance System sites in Ghana, Guinea-Bissau, Ethiopia, Uganda and Bangladesh (2017-2018). We investigated responses to survey questions regarding pregnancy intention in two ways: (i) pregnancy-specific intention and (ii) desired-versus-actual family size. We assessed data completeness for each and level of agreement between the two questions, and with future fertility desire. We analysed associations between pregnancy intention and number and timing of antenatal care visits, place of delivery, and stillbirth, neonatal death and low birthweight.
Missing data were <2% in all questions. Responses to pregnancy-specific questions were more consistent with future fertility desire than desired-versus-actual family size responses. Using the pregnancy-specific questions, 7.4% of women who reported their last pregnancy as unwanted reported wanting more children in the future, compared with 45.1% of women in the corresponding desired family size category. Women reporting unintended pregnancies were less likely to attend 4+ antenatal care visits (aOR 0.73, 95% CI 0.64-0.83), have their first visit during the first trimester (aOR 0.71, 95% CI 0.63-0.79), and report stillbirths (aOR 0.57, 95% CI 0.44-0.73) or neonatal deaths (aOR 0.79, 95% CI 0.64-0.96), compared with women reporting intended pregnancies. We found no associations for desired-versus-actual family size intention.
We found the pregnancy-specific intention questions to be a much more reliable assessment of pregnancy intention than the desired-versus-actual family size questions, despite a reluctance to report pregnancies as unwanted rather than mistimed. The additional questions were useful and may complement current DHS questions, although these are not the only possibilities. As women with unintended pregnancies were more likely to miss timely and frequent antenatal care, implementation research is required to improve coverage and quality of care for those women.
Objectives
We compared pregnancy identification methods and outcome capture across 31 Health Demographic Surveillance System (HDSS) sites in 14 countries in sub-Saharan Africa and Asia.
Methods
From ...2009 to 2014, details on the sites and surveillance systems including frequency of update rounds, characteristics of enumerators and interviewers, acceptable respondents were collected and compared across sites.
Results
The 31 HDSS had a combined population of over 2,905,602 with 165,820 births for the period. Stillbirth rate ranged from 1.9 to 42.6 deaths per 1000 total births and the neonatal mortality rate from 2.6 to 41.6 per 1000 live births. Three quarters (75.3%) of recorded neonatal deaths occurred in the first week of life. The proportion of infant deaths that occurred in the neonatal period ranged from 8 to 83%, with a median of 53%. Sites that registered pregnancies upon locating a live baby in the routine household surveillance round had lower recorded mortality rates.
Conclusions
Increased attention and standardization of pregnancy surveillance and the time of birth will improve data collection and provide platforms for evaluations and availability of data for decision-making with implications for national planning.
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