Impact of computer-aided detection prompts on the sensitivity and specificity of screening mammography.

OBJECTIVES To determine the value of computer-aided detection (CAD) for breast cancer screening. DESIGN Two sets of mammograms with known outcomes were used in two studies. Participants in both studies read the films with and without the benefit of a computer aid. In both studies, the order of reading sessions was randomised separately for each reader. The first set of 180 films, used in study 1, included 20 false-negative interval cancers and 40 screen-detected cancers. The second set of 120 films, used in study 2, was designed to be favourable to CAD: all 44 cancer cases had previously been missed by a film reader and cancers prompted by CAD were preferentially included. SETTING The studies were conducted at five UK screening centres between January 2001 and April 2003. PARTICIPANTS Thirty radiologists, five breast clinicians and 15 radiographers participated. INTERVENTIONS All cases in the trial were digitised and analysed using the R2 ImageChecker version 2.2. Participants all received training on the use of CAD. In the intervention condition, participants interpreted cases with a prompt sheet on which regions of potential abnormality were indicated. MAIN OUTCOME MEASURES The sensitivity and specificity of participants were measured in both intervention and control conditions. RESULTS No significant difference was found for readers' sensitivity or specificity between the prompted and unprompted conditions in study 1 [95% confidence index (CI) for sensitivity with and without CAD is 0.76 to 0.80, for specificity it is 0.81 to 0.86 without CAD and 0.81 to 0.87 with CAD]. No statistically significant difference was found between the sensitivity and specificity of different groups of film reader (95% CI for unprompted sensitivity of radiologists was 0.75 to 0.81, for radiographers it was 0.71 to 0.81, prompted sensitivity was 0.76 to 0.81 for radiologists and 0.69 to 0.79 for radiographers). Thirty-five readers participated in study 2. Sensitivity was improved in the prompted condition (0.81 from 0.78) but the difference was slightly below the threshold for statistical significance (95% CI for the difference -0.003 to 0.064). Specificity also improved (0.87 from 0.86); again, the difference was not significant at 0.05 (95% CI -0.003 to 0.034). A cost-effectiveness analysis showed that computer prompting increases cost. CONCLUSIONS No significant improvement in film readers' sensitivity or specificity or gain in cost-effectiveness was established in either study. This may be due to the system's low specificity, its relatively poor sensitivity for subtle cancers or the fact the prompts cannot serve as aids to decision-making. Readers may have been better able to make use of the prompts after becoming more accustomed to working with them. Prompts may have an impact in routine use that is not detectable in an experimental setting. Although the case for CAD as an element of the NHS Breast Screening Programme is not made here, further research is required. Evaluations of new CAD tools in routine use are underway and their results should be given careful attention.

[1]  K Johnston,et al.  Modelling the future costs of breast screening. , 2001, European journal of cancer.

[2]  I. Ellis,et al.  Pathological prognostic factors in breast cancer. , 1999, Critical reviews in oncology/hematology.

[3]  R. Warren,et al.  Mammography screening: an incremental cost effectiveness analysis of double versus single reading of mammograms , 1996, BMJ.

[4]  R. Blamey,et al.  Potential for cost economies in guiding therapy in patients with metastatic breast cancer. , 1995, British Journal of Cancer.

[5]  H. D. de Koning,et al.  Prediction of the effects and costs of breast‐cancer screening in Germany , 1994, International journal of cancer.

[6]  E. Egge,et al.  Computed assisted detection of interval breast cancers. , 2001, European journal of radiology.

[7]  I. Ellis,et al.  Local recurrence after simple mastectomy , 1994, The British journal of surgery.

[8]  R. Brem,et al.  Radiologist detection of microcalcifications with and without computer-aided detection: a comparative study. , 2001, Clinical radiology.

[9]  M S Pepe,et al.  Design of a study to improve accuracy in reading mammograms. , 1997, Journal of clinical epidemiology.

[10]  Jackie Brown,et al.  UK Breast Screening Programme: How Does it Reflect the Forrest Recommendations? , 1997, Journal of medical screening.

[11]  I. Ellis,et al.  Safe selection criteria for breast conservation without radical excision in primary operable invasive breast cancer. , 1995, European journal of cancer.

[12]  T. Freer,et al.  Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center. , 2001, Radiology.

[13]  Digital mammography: a model for assessing cost-effectiveness. , 1998, Academic radiology.

[14]  C. Rutter,et al.  Assessing mammographers' accuracy. A comparison of clinical and test performance. , 2000, Journal of clinical epidemiology.

[15]  W. Odling-Smee,et al.  Screening for Breast Cancer , 1985, The Lancet.

[16]  農林水産奨励会農林水産政策情報センター,et al.  The green book : appraisal and evaluation in central government , 2003 .

[17]  R. Blamey 4. The design and clinical use of the nottingham prognostic index in breast cancer , 1996 .

[18]  N. Wald,et al.  UKCCCR multicentre randomised controlled trial of one and two view mammography in breast cancer screening , 1995, BMJ.

[19]  R. Given-Wilson,et al.  Observer variability in cancer detection during routine repeat (incident) mammographic screening in a study of two versus one view mammography , 1999, Journal of medical screening.

[20]  C. J. Rosenquist,et al.  The cost-effectiveness of mammographic screening strategies. , 1995, JAMA.

[21]  J Brown,et al.  Two view mammography at incident screens: cost effectiveness analysis of policy options , 1999, BMJ.

[22]  一郎 大久保 Cost-effectiveness analysis of mass screening for breast cancer in Japan , 1993 .

[23]  P. Skrabanek The Cost-effectiveness of Breast Cancer Screening , 1991, International Journal of Technology Assessment in Health Care.

[24]  C. J. Rosenquist,et al.  Screening mammography beginning at age 40 years , 1998, Cancer.

[25]  A. Briggs,et al.  Probabilistic Sensitivity Analysis for Decision Trees with Multiple Branches: Use of the Dirichlet Distribution in a Bayesian Framework , 2003, Medical decision making : an international journal of the Society for Medical Decision Making.

[26]  C. Beam,et al.  Variability in the interpretation of screening mammograms by US radiologists. Findings from a national sample. , 1996, Archives of internal medicine.

[27]  M J Al,et al.  Costs, effects and C/E-ratios alongside a clinical trial. , 1994, Health economics.

[28]  K. Kerlikowske,et al.  Cost-Effectiveness of Extending Screening Mammography Guidelines To Include Women 40 to 49 Years of Age , 1997, Annals of Internal Medicine.

[29]  F. Antoñanzas,et al.  Economic evaluation of a mammography-based breast cancer screening programme in Spain , 1997 .

[30]  J. Richardson,et al.  A cost utility analysis of mammography screening in Australia. , 1992, Social science & medicine.

[31]  B E Hillner,et al.  Efficacy and cost effectiveness of adjuvant chemotherapy in women with node-negative breast cancer. A decision-analysis model. , 1991, The New England journal of medicine.

[32]  Jonathan Karnon,et al.  Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation. , 2003, Health economics.

[33]  R. Warren,et al.  Mammography screening: an incremental cost effectiveness analysis of two view versus one view procedures in London. , 1995, Journal of epidemiology and community health.

[34]  I. O. Ellis,et al.  Confirmation of a prognostic index in primary breast cancer. , 1987, British Journal of Cancer.

[35]  B. McNeil,et al.  Probabilistic Sensitivity Analysis Using Monte Carlo Simulation , 1985, Medical decision making : an international journal of the Society for Medical Decision Making.