PROMISE: Working with the CF community to understand emerging clinical and research needs for those treated with highly effective CFTR modulator therapy

Highly effective CFTR modulator drug therapy is increasingly available to those with cystic fibrosis. Multiple observational research studies are now being conducted to better understand the impacts of this important therapeutic milestone on long-term outcomes, patient care needs, and future research priorities. PROMISE is a large, multi-disciplinary academic study focused on the broad impacts of starting elexacaftor/tezacaftor/ivacaftor in the US population age 6 years and older. The many areas of investigation and rationale for each are discussed by organ systems, along with recognition of remaining important questions that will not be addressed by this study alone. Knowledge gained through this and multiple complementary studies around the world will help to understand important health outcomes, clinical care priorities, and research needs for a large majority of people treated with these or similarly effective medications targeting the primary cellular impairment in cystic fibrosis.     

Extracting data from electronic medical records: validation of a natural language processing program to assess prostate biopsy results

Objective

The extraction of specific data from electronic medical records (EMR) remains tedious and is often performed manually. Natural language processing (NLP) programs have been developed to identify and extract information within clinical narrative text. We performed a study to assess the validity of an NLP program to accurately identify patients with prostate cancer and to retrieve pertinent pathologic information from their EMR.

Materials and methods

A retrospective review was performed of a prospectively collected database including patients from the Southern California Kaiser Permanente Medical Region that underwent prostate biopsies during a 2-week period. A NLP program was used to identify patients with prostate biopsies that were positive for prostatic adenocarcinoma from all pathology reports within this period. The application then processed 100 consecutive patients with prostate adenocarcinoma to extract 10 variables from their pathology reports. The extraction and retrieval of information by NLP was then compared to a blinded manual review.

Results

A consecutive series of 18,453 pathology reports were evaluated. NLP correctly detected 117 out of 118 patients (99.1 %) with prostatic adenocarcinoma after TRUS-guided prostate biopsy. NLP had a positive predictive value of 99.1 % with a 99.1 % sensitivity and a 99.9 % specificity to correctly identify patients with prostatic adenocarcinoma after biopsy. The overall ability of the NLP application to accurately extract variables from the pathology reports was 97.6 %.

Conclusions

Natural language processing is a reliable and accurate method to identify select patients and to extract relevant data from an existing EMR in order to establish a prospective clinical database.     

Survival after minimally invasive vs. open radical nephrectomy for stage I and II renal cell carcinoma

International Journal of Clinical Oncology - A recently reported phase III randomized trial comparing open and minimally invasive hysterectomy showed significantly higher rates of local recurrence...     

Risk of type 2 diabetes among individuals with high and low glomerular filtration rates

Aims/hypothesis  Metabolic abnormalities frequently develop prior to the diagnosis of type 2 diabetes and chronic kidney disease. However, it is not known whether GFR predicts the onset of type 2 diabetes. Methods  Incident diabetes was ascertained in the Insulin Resistance Atherosclerosis Study (IRAS) (n = 864; age 40–69 years; median follow-up 5.2 years [4.5–6.6 years]; 141 incident cases of diabetes). GFR was estimated by the Modification of Diet in Renal Disease equation. We assessed the relationship between GFR and incident diabetes by logistic regression analysis. Results were adjusted for age, sex, ethnicity, clinic location, BMI, systolic blood pressure, antihypertensive treatment, family history of diabetes, insulin sensitivity and secretion, albumin to creatinine ratio, and levels of triacylglycerols, HDL-cholesterol, plasminogen activator inhibitor-1, and fasting and 2 h glucose. Results  The relationship between GFR and incident diabetes was not linear. This relationship was statistically significant (p = 0.039) using a restricted cubic polynomial spline for GFR as a regression modelling strategy. Participants were stratified by GFR quintiles. Mean values for GFR from the first to the fifth quintile were 60.8, 71.6, 79.8, 88.2 and 109.0 ml min⁻¹ 1.73 m⁻². Relative to the fourth quintile, the odds ratios of incident diabetes for the first, second, third and fifth quintiles were 2.32 (95% CI 1.06–5.05), 1.76 (95% CI 0.80–3.88), 1.26 (95% CI 0.56–2.84) and 2.59 (95% CI 1.18–5.65), respectively. Conclusions/interpretation  Individuals in the upper and lower ranges of GFR are at increased risk of future diabetes. GFR and type 2 diabetes may share common pathogenic mechanisms.