Publications

BACKGROUND AND STUDY AIMS

The learning curve for optical diagnosis of colorectal polyps with the narrow-band imaging (NBI) is unknown. To forego histological analysis of diminutive polyps diagnosed optically with high confidence, guidelines recommend ≥ 90 % negative predictive value (NPV) and concordance of ≥ 90 % for surveillance intervals predicted optically and histologically. We aimed to study the learning of optical diagnosis for colorectal polyps.

PATIENTS AND METHODS

We studied five endoscopists as part of a randomized multisite trial comparing near-focus and standard-focus views for optical diagnosis. They trained using a computer-based module, followed by 10 real-time colonoscopies with pathology correlation. Endoscopists then optically diagnosed and resected all the polyps found during 558 consecutive colonoscopies, and diagnoses were compared with pathology. Endoscopists repeated the training module at the study midpoint. NPV and concordance of surveillance intervals for diminutive polyps diagnosed optically with high confidence were measured over time.

RESULTS

Endoscopists showed high diagnostic performance, with a nonsignificant trend toward higher NPV in the second half of the study. For the 445 polyps in the standard-view arm, the NPV was 88.0 % (95 %CI 75.7 % - 95.5 %) in the first half and 95.8 % (88.3 % - 99.1 %) in the second; P = 0.7. Three endoscopists in the first half and four in the second achieved > 90 % NPV. Concordance of surveillance intervals was identical in the first and second halves at 98.1 % (95 %CI 93.3 % - 99.8 %).

CONCLUSIONS

High NPV for the prediction of non-neoplasms with NBI was achieved and maintained in this group of endoscopists who participated in standardized and continued training. Both NPV and surveillance interval agreement indicated high performance in the optical diagnosis of colorectal polyps and exceeded thresholds.

Education, justification, and optimization are the cornerstones to enhancing the radiation safety of medical imaging. Education regarding the benefits and risks of imaging and the principles of radiation safety is required for all clinicians in order for them to be able to use imaging optimally. Empowering patients with knowledge of the benefits and risks of imaging will facilitate their meaningful participation in decisions related to their health care, which is necessary to achieve patient-centered care. Limiting the use of imaging to appropriate clinical indications can ensure that the benefits of imaging outweigh any potential risks. Finally, the continually expanding repertoire of techniques that allow high-quality imaging with lower radiation exposure should be used when available to achieve safer imaging. The implementation of these strategies in practice is necessary to achieve high-quality, patient-centered imaging and will require a shared effort and investment by all stakeholders, including physicians, patients, national scientific and educational organizations, politicians, and industry.

BACKGROUND

Guidelines recommend incorporating life expectancy (LE) into clinical decision-making for preventive interventions such as cancer screening. Previous research focused on mortality risk (e.g. 28% at 4 years) which is more difficult to interpret than LE (e.g. 7.3 years) for both patients and clinicians. Our objective was to utilize the Gompertz Law of Human Mortality which states that mortality risk doubles in a fixed time interval to transform the Lee mortality index into a LE calculator.

METHODS

We examined community-dwelling older adults age 50 and over enrolled in the nationally representative 1998 wave of the Health and Retirement Study or HRS (response rate 81%), dividing study respondents into development (n = 11701) and validation (n = 8009) cohorts. In the development cohort, we fit proportional hazards Gompertz survival functions for each of the risk groups defined by the Lee mortality index. We validated our LE estimates by comparing our predicted LE with observed survival in the HRS validation cohort and an external validation cohort from the 2004 wave of the English Longitudinal Study on Ageing or ELSA (n = 7042).

RESULTS

The ELSA cohort had a lower 8-year mortality risk (14%) compared to our HRS development (23%) and validation cohorts (25%). Our model had good discrimination in the validation cohorts (Harrell's c 0.78 in HRS and 0.80 in the ELSA). Our predicted LE's were similar to observed survival in the HRS validation cohort without evidence of miscalibration (Hosmer-Lemeshow, p = 0.2 at 8 years). However, our predicted LE's were longer than observed survival in the ELSA cohort with evidence of miscalibration (Hosmer-Lemeshow, p<0.001 at 8 years) reflecting the lower mortality rate in ELSA.

CONCLUSION

We transformed a previously validated mortality index into a LE calculator that incorporated patient-level risk factors. Our LE calculator may help clinicians determine which preventive interventions are most appropriate for older US adults.