Updating Photon-Based Normal Tissue Complication Probability Models for Pneumonitis in Patients With Lung Cancer Treated With Proton Beam Therapy

Purpose: No validated models for predicting the risk of radiation pneumonitis (RP) with proton beam therapy (PBT) currently exist. Our goal was to externally validate and recalibrate multiple established photon-based normal tissue complication probability models for RP in a cohort with locally advanced nonsmall cell lung cancer treated with contemporary doses of chemoradiation using PBT. Methods and Materials: The external validation cohort consisted of 99 consecutive patients with locally advanced nonsmall cell lung cancer treated with chemoradiation using PBT. RP was retrospectively scored at 3 and 6 months posttreatment. We evaluated the performance of the photon Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) pneumonitis model, the QUANTEC model adjusted for clinical risk factors, and the newer Netherlands updated QUANTEC model. A closed testing procedure was performed to test the need for model updating, either by recalibration-in-the-large (re-estimation of intercept), recalibration (re-estimation of intercept/slope), or model revision (re-estimation of all coefficients). Results: There were 21 events (21%) of ≥grade 2 RP. The closed testing procedure on the PBT data set did not detect major deviations between the models and the data and recommended adjustment of the intercept only for the photon-based Netherlands updated QUANTEC model (intercept update: –1.2). However, an update of the slope and revision of the model coefficients were not recommended by the closed testing procedure, as the deviations were not significant within the power of the data. Conclusions: The similarity between the dose-response relationship for PBT and photons for normal tissue complications has been an assumption until now. We demonstrate that the preexisting, widely used photon based models fit our PBT data well with minor modifications. These now-validated and updated normal tissue complication probability models can aid in individualizing selection of the most optimal treatment technique for a particular patient

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Trends in Respiratory Syncytial Virus and Bronchiolitis Hospitalization Rates in High-Risk Infants in a United States Nationally Representative Database, 1997–2012

<div><p>Background</p><p>Respiratory syncytial virus (RSV) causes significant pediatric morbidity and is the most common cause of bronchiolitis. Bronchiolitis hospitalizations declined among US infants from 2000‒2009; however, rates in infants at high risk for RSV have not been described. This study examined RSV and unspecified bronchiolitis (UB) hospitalization rates from 1997‒2012 among US high-risk infants.</p><p>Methods</p><p>The Kids’ Inpatient Database (KID) infant annual RSV (<i>ICD-9</i> 079.6, 466.11, 480.1) and UB (<i>ICD-9</i> 466.19, 466.1) hospitalization rates were estimated using weighted counts. Denominators were based on birth hospitalizations with conditions associated with high-risk for RSV: chronic perinatal respiratory disease (chronic lung disease [CLD]); congenital airway anomalies (CAA); congenital heart disease (CHD); Down syndrome (DS); and other genetic, metabolic, musculoskeletal, and immunodeficiency conditions. Preterm infants could not be identified. Hospitalizations were characterized by mechanical ventilation, inpatient mortality, length of stay, and total cost (2015$). Poisson and linear regression were used to test statistical significance of trends.</p><p>Results</p><p>RSV and UB hospitalization rates were substantially elevated for infants with higher-risk CHD, CLD, CAA and DS without CHD compared with all infants. RSV rates declined by 47.0$31,742 and $25,962, respectively, and RSV mortality declined to 0.9%.</p><p>Conclusions</p><p>Among high-risk infants between 1997 and 2012, RSV hospitalization rates declined among CLD and higher-risk CHD infants, coincident with widespread RSV immunoprophylaxis use in these populations. UB hospitalization rates increased in all high-risk groups except higher-risk CHD, suggesting improvement in the health status of higher-risk CHD infants, potentially due to enhanced surgical interventions. Mechanical ventilation use and RSV and UB hospitalization costs increased while RSV mortality declined.</p></div

<i>ICD-9-CM</i> Codes for Conditions Associated With High-Risk for Respiratory Syncytial Virus Disease and Weighted Estimates of Overall Infant Hospitalization from KID, 1997–2012.

<p><i>ICD-9-CM</i> Codes for Conditions Associated With High-Risk for Respiratory Syncytial Virus Disease and Weighted Estimates of Overall Infant Hospitalization from KID, 1997–2012.</p

Rate of Hospitalizations due to Respiratory Syncytial Virus (RSV) or Unspecified Bronchiolitis (UB) According to High-Risk Status in KID, 1997–2012.

<p>Rate of Hospitalizations due to Respiratory Syncytial Virus (RSV) or Unspecified Bronchiolitis (UB) According to High-Risk Status in KID, 1997–2012.</p

Hospitalized Illness Severity Indicators Among Infant Hospitalizations for Unspecified Bronchiolitis in KID, 1997−2012.

<p>Hospitalized Illness Severity Indicators Among Infant Hospitalizations for Unspecified Bronchiolitis in KID, 1997−2012.</p

A Natural Language Processing–Assisted Extraction System for Gleason Scores: Development and Usability Study

BackgroundNatural language processing (NLP) offers significantly faster variable extraction compared to traditional human extraction but cannot interpret complicated notes as well as humans can. Thus, we hypothesized that an “NLP-assisted” extraction system, which uses humans for complicated notes and NLP for uncomplicated notes, could produce faster extraction without compromising accuracy. ObjectiveThe aim of this study was to develop and pilot an NLP-assisted extraction system to leverage the strengths of both human and NLP extraction of prostate cancer Gleason scores. MethodsWe collected all available clinical and pathology notes for prostate cancer patients in an unselected academic biobank cohort. We developed an NLP system to extract prostate cancer Gleason scores from both clinical and pathology notes. Next, we designed and implemented the NLP-assisted extraction system algorithm to categorize notes into “uncomplicated” and “complicated” notes. Uncomplicated notes were assigned to NLP extraction and complicated notes were assigned to human extraction. We randomly reviewed 200 patients to assess the accuracy and speed of our NLP-assisted extraction system and compared it to NLP extraction alone and human extraction alone. ResultsOf the 2051 patients in our cohort, the NLP system extracted a prostate surgery Gleason score from 1147 (55.92%) patients and a prostate biopsy Gleason score from 1624 (79.18%) patients. Our NLP-assisted extraction system had an overall accuracy rate of 98.7%, which was similar to the accuracy of human extraction alone (97.5%; P=.17) and significantly higher than the accuracy of NLP extraction alone (95.3%; P<.001). Moreover, our NLP-assisted extraction system reduced the workload of human extractors by approximately 95%, resulting in an average extraction time of 12.7 seconds per patient (vs 256.1 seconds per patient for human extraction alone). ConclusionsWe demonstrated that an NLP-assisted extraction system was able to achieve much faster Gleason score extraction compared to traditional human extraction without sacrificing accuracy

Patient Characteristics of Hospitalized Non-Birth Infants in KID, 1997 to 2012.

<p>Patient Characteristics of Hospitalized Non-Birth Infants in KID, 1997 to 2012.</p

Planning for Resilience and Reducing Risk: Lessons for Mexico City

Disaster risk management (DRM) has never been as essential to Mexico City as today. Three years ago, the city was hit with its largest earthquake in over 30 years. It killed 219 people, caused billions of dollars in infrastructure damages, and left a vibrant city in disarray. While Mexico City and its surrounding communities continue to recover, the aftermath of the earthquake confronts its residents, businesses, and local leaders daily

Hospitalization Rates due to Respiratory Syncytial Virus by High-Risk Comorbidities Among Infants in KID, 1997–2012.

<p>Hospitalization Rates due to Respiratory Syncytial Virus by High-Risk Comorbidities Among Infants in KID, 1997–2012.</p