Extrapolating parametric survival models in health technology assessment : a simulation study

Extrapolations of parametric survival models fitted to censored data are routinely used in the assessment of health technologies to estimate mean survival, particularly in diseases that potentially reduce the life expectancy of patients. Akaike’s information criterion (AIC) and Bayesian information criterion (BIC) are commonly used in health technology assessment alongside an assessment of plausibility to determine which statistical model best fits the data and should be used for prediction of long-term treatment effects. We compare fit and estimates of restricted mean survival time (RMST) from 8 parametric models and contrast models preferred in terms of AIC, BIC, and log-likelihood, without considering model plausibility. We assess the methods’ suitability for selecting a parametric model through simulation of data replicating the follow-up of intervention arms for various time-to-event outcomes from 4 clinical trials. Follow-up was replicated through the consideration of recruitment duration and minimum and maximum follow-up times. Ten thousand simulations of each scenario were performed. We demonstrate that the different methods can result in disagreement over the best model and that it is inappropriate to base model selection solely on goodness-of-fit statistics without consideration of hazard behavior and plausibility of extrapolations. We show that typical trial follow-up can be unsuitable for extrapolation, resulting in unreliable estimation of multiple parameter models, and infer that selecting survival models based only on goodness-of-fit statistics is unsuitable due to the high level of uncertainty in a cost-effectiveness analysis. This article demonstrates the potential problems of overreliance on goodness-of-fit statistics when selecting a model for extrapolation. When follow-up is more mature, BIC appears superior to the other selection methods, selecting models with the most accurate and least biased estimates of RMST

Extrapolating parametric survival models in Health Technology Assessment using model averaging : a simulation study

Previous work examined the suitability of relying on routine methods of model selection when extrapolating survival data in a health technology appraisal setting. Here we explore solutions to improve reliability of restricted mean survival time (RMST) estimates from trial data by assessing model plausibility and implementing model averaging. We compare our previous methods of selecting a model for extrapolation using the Akaike information criterion (AIC) and Bayesian information criterion (BIC). Our methods of model averaging include using equal weighting across models falling within established threshold ranges for AIC and BIC and using BIC-based weighted averages. We apply our plausibility assessment and implement model averaging to the output of our previous simulations, where 10,000 runs of 12 trial-based scenarios were examined. We demonstrate that removing implausible models from consideration reduces the mean squared error associated with the restricted mean survival time (RMST) estimate from each selection method and increases the percentage of RMST estimates that were within 10% of the RMST from the parameters of the sampling distribution. The methods of averaging were superior to selecting a single optimal extrapolation, aside from some of the exponential scenarios where BIC already selected the exponential model. The averaging methods with wide criterion-based thresholds outperformed BIC-weighted averaging in the majority of scenarios. We conclude that model averaging approaches should feature more widely in the appraisal of health technologies where extrapolation is influential and considerable uncertainty is present. Where data demonstrate complicated underlying hazard rates, funders should account for the additional uncertainty associated with these extrapolations in their decision making. Extended follow-up from trials should be encouraged and used to review prices of therapies to ensure a fair price is paid

Biased survival predictions when appraising health technologies in heterogeneous populations

Introduction Time-to-event data from clinical trials are routinely extrapolated using parametric models to estimate the cost effectiveness of novel therapies, but how this approach performs in the presence of heterogeneous populations remains unknown. Methods We performed a simulation study of seven scenarios with varying exponential distributions modelling treatment and prognostic effects across subgroup and complement populations, with follow-up typical of clinical trials used to appraise the cost effectiveness of therapies by agencies such as the UK National Institute for Health and Care Excellence (NICE). We compared established and emerging methods of estimating population life-years (LYs) using parametric models. We also proved analytically that an exponential model fitted to censored heterogeneous survival times sampled from two distinct exponential distributions will produce a biased estimate of the hazard rate and LYs. Results LYs are underestimated by the methods in the presence of heterogeneity, resulting in either under- or overestimation of the incremental benefit. In scenarios where the overestimation of benefit is likely, which is of interest to the healthcare provider, the method of taking the average LYs from all plausible models has the least bias. LY estimates from complete Kaplan–Meier curves have high variation, suggesting mature data may not be a reliable solution. We explore the effect of increasing trial sample size and accounting for detected treatment–subgroup interactions. Conclusions The bias associated with heterogeneous populations suggests that NICE may need to be more cautious when appraising therapies and to consider model averaging or the separate modelling of subgroups when heterogeneity is suspected or detected

Healthcare-use for Major Infectious Disease Syndromes in an Informal Settlement in Nairobi, Kenya

A healthcare-use survey was conducted in the Kibera informal settlement in Nairobi, Kenya, in July 2005 to inform subsequent surveillance in the site for infectious diseases. Sets of standardized questionnaires were administered to 1,542 caretakers and heads of households with one or more child(ren) aged less than five years. The average household-size was 5.1 (range 1-15) persons. Most (90%) resided in a single room with monthly rents of US$ 4.50-7.00. Within the previous two weeks, 49% of children (n=1,378) aged less than five years (under-five children) and 18% of persons (n=1,139) aged ≥5 years experienced febrile, diarrhoeal or respiratory illnesses. The large majority (>75%) of illnesses were associated with healthcare-seeking. While licensed clinics were the most-frequently visited settings, kiosks, unlicensed care providers, and traditional healers were also frequently visited. Expense was cited most often (50%) as the reason for not seeking healthcare. Of those who sought healthcare, 34-44% of the first and/or the only visits were made with non-licensed care providers, potentially delaying opportunities for early optimal intervention. The proportions of patients accessing healthcare facilities were higher with diarrhoeal disease and fever (but not for respiratory diseases in under-five children) than those reported from a contemporaneous study conducted in a rural area in Kenya. The findings support community-based rather than facility-based surveillance in this setting to achieve objectives for comprehensive assessment of the burden of disease

Retooling Cotton Growers for Improved Productivity in Mozambique: Implications of Integrated Crop Management Practices

In Mozambique average yields of seed cotton range from 400-750 kg/ha on smallholders’ farms, while those in research plots average 3,000 kg/ha. To improve productivity, integrated crop management (ICM) practices were promoted in cotton production systems, using farmer field schools (FFS). In addition, relevant information on cotton marketing was provided to the cotton growers. This paper examines the extent to which the initiative contributed to changes in farmer practices, productivity and income. The ICM farmers had significantly larger area (p<0.01) under cotton, which was due to an overall average increase of 0.19 ha above that of non-ICM farmers. Ninety seven per cent of the ICM farmers rated cotton as the key contributor to income compared to 80% of the non-ICM farmers. Net incomes from cotton were significantly higher (p<0.01) for the ICM farmers. The ICM farmers had better access to information and knowledge of cotton production compared to the other farmers. The ICM farmers used significantly (p<0.01) less pesticides by up to US$ 9.27 and realized better seed cotton yields of up to 250 kg/ha above non-ICM farmers. Efficient use of ICM practices contributed to sustained increase in productivity and incomes. Keywords: Productivity, sustainability, yield, income, pesticides

Scopes of practice for advanced practice nursing and advanced practice midwifery in Kenya:A gap analysis

BACKGROUND: There is increasing global evidence on the impact of advanced nursing and midwifery practitioners, and Kenya's healthcare system has an excellent opportunity to develop scopes of practice and other regulatory frameworks for the integration of these roles.OBJECTIVE: The primary purpose of this gap analysis was to explore the existing evidence on opportunities and threats toward the integration of the advanced practice nursing (APN) and advanced practice midwifery (APM) roles in Kenya's healthcare system.METHODS: The study team conducted a structured electronic database search of PubMed, CINAHL, Scopus, EBSCOhost Academic Search Complete, and PsycINFO to retrieve articles and credible websites for reports highlighting the opportunities and threats toward the integration of the APN and APM roles in Kenya's healthcare systems. The retrieved articles were screened for relevance and synthesized for reporting using the traditional literature review approach.RESULTS: The Kenya Health Policy Framework 2014-2030, growing population needs, and implementation of universal health coverage provide an opportunity to harness and leverage advanced practice roles in nursing and midwifery. There is also momentum to develop advanced practice because of strategic alliances and global evidence showing the contributions and quality of services offered by advanced practice nurses and advanced practice midwives. However, lack of financial support, structural challenges, and lack of national policies, regulations, and legislation continue to obstruct progress.CONCLUSION AND IMPLICATIONS FOR NURSING POLICY: Developing scopes of practice for APN and APM in Kenya will benefit the professions, the country's healthcare delivery system, and the population. Achieving universal health coverage depends on a health workforce trained and practicing at optimal levels in tandem with education and training to deliver quality care.</p

Healthcare-use for Major Infectious Disease Syndromes in an Informal Settlement in Nairobi, Kenya

A healthcare-use survey was conducted in the Kibera informal settlement in Nairobi, Kenya, in July 2005 to inform subsequent surveillance in the site for infectious diseases. Sets of standardized questionnaires were administered to 1,542 caretakers and heads of households with one or more child(ren) aged less than five years. The average household-size was 5.1 (range 1-15) persons. Most (90%) resided in a single room with monthly rents of US$ 4.50-7.00. Within the previous two weeks, 49% of children (n=1,378) aged less than five years (under-five children) and 18% of persons (n=1,139) aged 655 years experienced febrile, diarrhoeal or respiratory illnesses. The large majority (&gt;75%) of illnesses were associated with healthcareseeking. While licensed clinics were the most-frequently visited settings, kiosks, unlicensed care providers, and traditional healers were also frequently visited. Expense was cited most often (50%) as the reason for not seeking healthcare. Of those who sought healthcare, 34-44% of the first and/or the only visits were made with non-licensed care providers, potentially delaying opportunities for early optimal intervention. The proportions of patients accessing healthcare facilities were higher with diarrhoeal disease and fever (but not for respiratory diseases in under-five children) than those reported from a contemporaneous study conducted in a rural area in Kenya. The findings support community-based rather than facility-based surveillance in this setting to achieve objectives for comprehensive assessment of the burden of disease

Implementing SLMTA in the Kenya National Blood Transfusion Service: lessons learned

Background: The Kenya National Blood Transfusion Service (KNBTS) is mandated to provide safe and sufficient blood and blood components for the country. In 2013, the KNBTS National Testing Laboratory and the six regional blood transfusion centres were enrolled in the Strengthening Laboratory Management Toward Accreditation (SLMTA) programme. The process was supported by Global Communities with funding from the United States Centers for Disease Control and Prevention. Methods: The SLMTA implementation at KNBTS followed the standard three-workshop series, on-site mentorships and audits. Baseline, midterm and exit audits were conducted at the seven facilities, using a standard checklist to measure progress. Given that SLMTA was designed for clinical and public health laboratories, key stakeholders, guided by Global Communities, tailored SLMTA materials to address blood transfusion services, and oriented trainers, auditors and mentors on the same. Results: The seven facilities moved from an average of zero stars at baseline to an average of three stars at the exit audit. The average baseline audit score was 38% (97 points), midterm 71% (183 points) and exit audit 79% (205 points). The Occurrence Management and Process Improvement quality system essential had the largest improvement (at 67 percentage points), from baseline to exit, whereas Facilities and Safety had the smallest improvement (at 31 percentage points). Conclusion: SLMTA can be an effective tool for preparing a blood transfusion service for accreditation. Key success factors included customising SLMTA to blood transfusion activities; sensitising trainers, mentors and auditors on operations of blood transfusion service; creating SLMTA champions in key departments; and integrating other blood transfusion-specific accreditation standards into SLMTA

Evaluation of fitness in F2 generations of Africa Biofortified Sorghum event 188 and weedy Sorghum bicolor ssp. drummondii

Background: Introgression of transgenes from crops to their wild species may enhance the adaptive advantage and therefore the invasiveness of and weedy forms. The study evaluated the effect of Africa Biofortified Sorghum (ABS) genes from ABS event 188 on the vegetative and reproductive features of the F2 populations derived from crosses with Sorghum bicolor subsp. drummondii. Results: F1 populations were obtained from reciprocal crosses involving ABS event 188 and its null segregant with inbred weedy parents from S. bicolor subsp. drummondii. Four F2 populations and four parental populations were raised in RCBD with 4 replications in a confined field plot for two seasons. Vegetative and reproductive traits were evaluated. The vigour shown in the F2 populations from the reciprocal crosses involving ABS event 188 and S. bicolor subsp. drummondii was similar to that in the crosses involving the null segregant and S. bicolor subsp. drummondii. Differences in vegetative and reproductive parameters were observed between the parental controls and the F2 populations. Examination of the above and below ground vegetative biomass showed lack of novel weedy related features like rhizomes. Conclusions: Therefore, release of crops with ABS 188 transgenes into cropping systems is not likely to pose a risk of conferring additional adaptive advantage in the introgressing populations. The interaction of ABS genes in weedy backgrounds will also not have an effect towards enhancing the weedy features in these populations