A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

AIM: To explore the performance in diabetic retinopathy (DR) screening of artificial intelligence (AI) system by evaluating the image quality of a handheld Optomed Aurora fundus camera in comparison to traditional tabletop fundus cameras and the diagnostic accuracy of DR of the two modalities. METHODS: Overall, 630 eyes were included from three centers and screened by a handheld camera (Aurora, Optomed, Oulu, Finland) and a table-top camera. Image quality was graded by three masked and experienced ophthalmologists. The diagnostic accuracy of the handheld camera and AI system was evaluated in assessing DR lesions and referable DR. RESULTS: Under nonmydriasis status, the handheld fundus camera had better image quality in centration, clarity, and visible range (1.47, 1.48, and 1.40) than conventional tabletop cameras (1.30, 1.28, and 1.18; P<0.001). Detection of retinal hemorrhage, hard exudation, and macular edema were comparable between the two modalities, in principle, with the area under the curve of the handheld fundus camera slightly lower. The sensitivity and specificity for the detection of referable DR with the handheld camera were 82.1% (95%CI: 72.1%-92.2%) and 97.4% (95%CI: 95.4%-99.5%), respectively. The performance of AI detection of DR using the Phoebus Algorithm was satisfactory; however, Phoebus showed a high sensitivity (88.2%, 95%CI: 79.4%-97.1%) and low specificity (40.7%, 95%CI: 34.1%-47.2%) when detecting referable DR. CONCLUSION: The handheld Aurora fundus camera combined with autonomous AI system is well-suited in DR screening without mydriasis because of its high sensitivity of DR detection as well as its image quality, but its specificity needs to be improved with better modeling of the data. Use of this new system is safe and effective in the detection of referable DR in real world practice.

Association between dietary nitrate and nitrite intake and sitespecific cancer risk: evidence from observational studies.

Epidemiological studies have reported inconsistent findings on the association between dietary nitrate and nitrite intake and cancer risk. We performed a meta-analysis of epidemiological studies to summarize available evidence on the association between dietary nitrate and nitrite intake and cancer risk from published prospective and case-control studies. PubMed database was searched to identify eligible publications through April 30th, 2016. Study-specific relative risks (RRs) with corresponding 95% confidence interval (CI) from individual studies were pooled by using random- or fixed- model, and heterogeneity and publication bias analyses were conducted. Data from 62 observational studies, 49 studies for nitrates and 51 studies for nitrites, including a total of 60,627 cancer cases were analyzed. Comparing the highest vs. lowest levels, dietary nitrate intake was inversely associated with gastric cancer risk (RR = 0.78; 95%CI = 0.67-0.91) with moderate heterogeneity (I2 = 42.3%). In contrast, dietary nitrite intake was positively associated with adult glioma and thyroid cancer risk with pooled RR of 1.21 (95%CI = 1.03-1.42) and 1.52 (95%CI = 1.12-2.05), respectively. No significant associations were found between dietary nitrate/nitrite and cancers of the breast, bladder, colorectal, esophagus, renal cell, non-Hodgkin lymphoma, ovarian, and pancreas. The present meta-analysis provided modest evidence that positive associations of dietary nitrate and negative associations of dietary nitrite with certain cancers.

Sex, Race, and Age Disparities in the Improvement of Survival for Gastrointestinal Cancer over Time.

There have been notable improvements in survival over the past 2 decades for gastrointestinal (GI) cancer. However, the degree of improvement by age, race, and sex remains unclear. We analyzed data from 9 population-based cancer registries included in the SEER program of the National Cancer Institute (SEER 9) in 1990 to 2009 (n = 288,337). The degree of survival improvement over time by age, race, and sex was longitudinally measured. From 1990 to 2009, improvements in survival were greater for younger age groups. For patients aged 20 to 49 years and diagnosed from 2005 to 2009, adjusted HRs (95% CIs) were 0.74 (95% CI, 0.66-0.83), 0.49 (95% CI, 0.37-0.64), 0.69 (95% CI, 0.65-0.76), 0.62 (95% CI, 0.54-0.69), and 0.56 (95% CI, 0.42-0.76), for cancer of the stomach, small intestine, colon, rectum and anus, respectively, compared with the same age groups of patients diagnosed during 1990 to 1994. Compared with African Americans, whites experienced greater improvement in small intestinal and anal cancer survival. Female anal cancer and regional anal cancer patients experienced no improvement. Our data suggest that different improvement in survival in age, sex and race exists.

Development of a preliminary nomogram to predict progression of bone scan for castration-resistant prostate cancer.

The optimal time to perform bone scan to detect new metastasis during the castration-resistant prostate cancer (CRPC) stage remains undefined. This study attempted to identify predictors of progression of bone scan for CRPC, and use such information to develop a nomogram to predict the optimal time of examinations for bone scan. The analysis included 167 CRPC patients. Progression of bone lesion, as evaluated by bone scan, occurred in 64 (38.3%) cases. A logistic regression identified the following three risk factors: short time to prostate-specific antigen (PSA) progression, severe pain, and short PSA doubling time (PSADT) (P<0.05 for all). A nomogram model was constructed to predict progression of bone scan using time to PSA progression and severe pain as dichotomized variables and PSADT as a continuous variable. The result indicated that a predictive nomogram model showed a bootstrap-corrected concordance index of 0.762 and good calibration using the three readily available variables, and there were worse prognosis and higher progression rate of bone scan for patients with time to PSA progression <6.6 months, severe pain, and short PSADT (<2 months). In conclusion, short time to PSA progression, severe pain, and short PSADT are three risk factors of progression of bone scan for CRPC patients. The predictive nomogram model may be a valuable numerical assessment tool for patient consultation and treatment decision.