A Case of Mistaken Identity? Measuring Rates of Improved Seed Adoption in Tanzania Using DNA Fingerprinting

Studies of improved seed adoption in developing countries are almost always based on household surveys and are premised on the assumption that farmers can accurately self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of seed varieties planted, or even whether the seed is local or improved, are sometimes inconsistent with the DNA fingerprinting results of those crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertiliser, and labour allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers’ seed type awareness may translate into suboptimal management practices. The average yield of seed that is correctly identified as improved is almost 700 kg per hectare greater than that of type I errors. This indicates that investments in farmers’ access to information, seed labelling, and seed system oversight are needed to complement investments in seed variety development.     

Value of clinical trial narrative data to estimate the costs of adverse event management: a feasibility study

Abstract

Aims: The objective of this feasibility study was to determine the extent to which data from randomized controlled trials (RCTs) may serve as a useful source for collecting health care resource use (HCRU) for the purposes of estimating costs of managing adverse events (AEs), specifically, grade 3–4 nausea and thrombocytopenia, which may be experienced during chemotherapy treatment.

Materials and Methods: The feasibility study was conducted in four steps: (1) HCRU data were extracted from patient narratives in four phase 3 RCTs in non–small cell lung cancer; (2) missing HCRU data were imputed; (3) unit costs were applied to the resulting HCRU data set and costs of managing AEs were estimated; and (4) the overall utility of using RCT data as a source for estimating costs of AEs was evaluated.

Results: 33 nausea and 68 thrombocytopenia AEs met eligibility criteria and were evaluated in this study. Medication usage was recorded as a treatment in 76% of nausea AEs, although only 14% of the instances of medication usage included the minimum data elements required for costing. Platelet transfusions were provided in 24% of thrombocytopenia AEs; however, in only one instance were the minimum data elements recorded. Of nausea and thrombocytopenia AEs, 18% and 72%, respectively, required no missing data assumptions or imputation.

Limitations: Only two AEs were considered, and they may not be representative of all AEs in terms of suitability for use in estimating HCRU and costs of managing AEs. Not all grade 3–4 AEs met the criteria for requiring a patient narrative. HCRU data in the narratives were incomplete.

Conclusions: The usefulness of RCTs for estimating the costs of AEs may be improved by using a standardized form to collect HCRU data for key AEs, including an appropriate level of detail required to estimate costs of managing the AEs.