OBJECTIVES: To assess the effectiveness and cost-effectiveness of adding automated image analysis to cervical screening programmes. DATA SOURCES: Searching of all major electronic databases to the end of 2000 was supplemented by a detailed survey for unpublished UK literature. METHOD: Four systematic reviews were conducted according to recognised guidance. The review of 'clinical effectiveness' included studies assessing reproducibility and impact on health outcomes and processes in addition to evaluations of test accuracy. A discrete event simulation model was developed, although the economic evaluation ultimately relied on a cost-minimisation analysis. RESULTS: The predominant finding from the systematic reviews was the very limited amount of rigorous primary research. None of the included studies refers to the only commercially available automated image analysis device in 2002, the AutoPap Guided Screening (GS) System. The results of the included studies were debatably most compatible with automated image analysis being equivalent in test performance to manual screening. Concerning process, there was evidence that automation does lead to reductions in average slide processing times. In the PRISMATIC trial this was reduced from 10.4 to 3.9 minutes, a statistically significant and practically important difference. The economic evaluation tentatively suggested that the AutoPap GS System may be efficient. The key proviso is that credible data become available to support that the AutoPap GS System has test performance and processing times equivalent to those obtained for PAPNET. CONCLUSIONS: The available evidence is still insufficient to recommend implementation of automated image analysis systems. The priority for action remains further research, particularly the 'clinical effectiveness' of the AutoPap GS System. Assessing the cost-effectiveness of introducing automation alongside other approaches is also a priority.
OBJECTIVES: To assess the effectiveness and cost-effectiveness of adding automated image analysis to cervical screening programmes. DATA SOURCES: Searching of all major electronic databases to the end of 2000 was supplemented by a detailed survey for unpublished UK literature. METHOD: Four systematic reviews were conducted according to recognised guidance. The review of 'clinical effectiveness' included studies assessing reproducibility and impact on health outcomes and processes in addition to evaluations of test accuracy. A discrete event simulation model was developed, although the economic evaluation ultimately relied on a cost-minimisation analysis. RESULTS: The predominant finding from the systematic reviews was the very limited amount of rigorous primary research. None of the included studies refers to the only commercially available automated image analysis device in 2002, the AutoPap Guided Screening (GS) System. The results of the included studies were debatably most compatible with automated image analysis being equivalent in test performance to manual screening. Concerning process, there was evidence that automation does lead to reductions in average slide processing times. In the PRISMATIC trial this was reduced from 10.4 to 3.9 minutes, a statistically significant and practically important difference. The economic evaluation tentatively suggested that the AutoPap GS System may be efficient. The key proviso is that credible data become available to support that the AutoPap GS System has test performance and processing times equivalent to those obtained for PAPNET. CONCLUSIONS: The available evidence is still insufficient to recommend implementation of automated image analysis systems. The priority for action remains further research, particularly the 'clinical effectiveness' of the AutoPap GS System. Assessing the cost-effectiveness of introducing automation alongside other approaches is also a priority.
Authors: G S Scotland; P McNamee; S Philip; A D Fleming; K A Goatman; G J Prescott; S Fonseca; P F Sharp; J A Olson Journal: Br J Ophthalmol Date: 2007-06-21 Impact factor: 4.638
Authors: Isaac Kinde; Chetan Bettegowda; Yuxuan Wang; Jian Wu; Nishant Agrawal; Ie-Ming Shih; Robert Kurman; Fanny Dao; Douglas A Levine; Robert Giuntoli; Richard Roden; James R Eshleman; Jesus Paula Carvalho; Suely Kazue Nagahashi Marie; Nickolas Papadopoulos; Kenneth W Kinzler; Bert Vogelstein; Luis A Diaz Journal: Sci Transl Med Date: 2013-01-09 Impact factor: 17.956