Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data

Introduction Recurrence free survival is frequently investigated in cancer outcome studies, however is not explicitly documented in cancer registry data that is widely used for research. Patterns of events after initial treatment such as oncology visits, re-operation, chemotherapy or radiation may herald recurrence. Objectives and Approach This study aimed to develop and validate algorithms for identifying breast cancer recurrence using large administrative data.Two cohorts with high recurrence rates were used: 1) all young (≤ 40 years) breast cancer patients (2007-2010), and 2) all neoadjuvant chemotherapy patients (2012-2014) in Alberta, Canada. Health events after primary treatment were obtained from the Alberta cancer registry, physician billing claims, and vital statistics databases. Positive recurrence status (defined as either locoregional, distant or both) was ascertained by primary chart review. The cohort was divided into a developing (60%) and validating (40%) set. Development of algorithms geared towards high sensitivity, PPV and accuracy respectively were performed using classification and regression tree (CART) models. Key variables in the models included: a new round of chemotherapy, a second mastectomy, and a new cluster of radiologist, oncologist or general surgeon visits occurring after the primary treatment. Compared with chart review data, the sensitivity, specificity, PPV, NPV and accuracy of the algorithms were calculated. Results Of 606 patients, 121 (20%) had recurrence after a median follow-up 4 years. The high sensitivity algorithm had 94.2% (95% CI: 90.1-98.4%) sensitivity, 92.8% (90.5-95.1%) specificity, 76.5% (70.0-88.3%) PPV, 98.5% (97.3-99.6%) NPV and 93.1% (91.0-95.1%) accuracy. The high PPV algorithm had 74.4% (66.6-82.2%) sensitivity, 97.8% (96.5-99.2%) specificity, 90.0% (84.1-95.9%) PPV, 93.6% (91.4-95.7%) NPV and 92.9% (90.9-95.0%) accuracy. The high accuracy algorithm had 88.4% (82.7-94.1%) sensitivity, 97.1% (95.6-98.6%) specificity, 88.4% (82.7-94.1%) PPV, 97.1% (95.6-98.6%) NPV and 95.4% (93.7-97.1%) accuracy. Conclusion/Implications The proposed algorithms achieved favourably high validity for identifying recurrence using widely available administrative data. Further study may be needed for improving sensitivity and PPV, and validating the algorithms in larger data for widespread use

Sleep architecture, periodic breathing and mood disturbance of expeditioners at Kunlun Station (4087 m) in Antarctica

Several studies have reported the detrimental impacts of hypoxia exposure on sleep. Chinese Kunlun Station (altitude 4087 m) is located at Dome A, the highest point on the Antarctic ice sheet and one of the most extreme environments on Earth. This study investigated alteration of sleep, breathing and mood status in healthy expeditioners at Kunlun Station at Dome A. The study examined 10 male volunteers of the inland transverse party to Kunlun Station during the 31st Chinese National Antarctic Research Expedition, and valid data from eight volunteers were analyzed. Sleep structure, breathing pattern and mood were monitored using portable polysomnography (PSG) and profile of mood state (POMS) at two time points: (1) at Zhongshan Station (10 m) before departure to Kunlun Station; (2) on nights 12 –13 of residence at Kunlun Station. Slow-wave sleep (Stage 3 non-rapid eye movement) was markedly reduced at Kunlun Station (P < 0.01). Total sleep time, sleep efficiency and sleep latency showed no significant changes. Total respiratory events (P < 0.05), apnea/hypopnea index (AHI) (P < 0.05) and hypopnea index (P < 0.01) substantially increased at Kunlun Station. The most common respiratory disorder was periodic breathing, occurring almost exclusively during non-rapid eye movement sleep. The oxygen desaturation index increased markedly (P < 0.05), while nocturnal oxygen saturation dramatically fell at Kunlun Station (P < 0.05). Vigor scores decreased at Kunlun Station (P < 0.05). Expeditioners exhibited reduced slow wave sleep, induced periodic breathing, decreased oxygen saturation and decreased vigor at Kunlun Station

Impact of pre-existing cardiovascular disease on treatment patterns and survival outcomes in patients with lung cancer

Abstract Background Baseline cardiovascular disease (CVD) can impact the patterns of treatment and hence the outcomes of patients with lung cancer. This study aimed to characterize treatment trends and survival outcomes of patients with pre-existing CVD prior to their diagnosis of lung cancer. Methods We conducted a retrospective, population-based cohort study of patients with lung cancer diagnosed from 2004 to 2015 in a large Canadian province. Multivariable logistic regression and Cox regression models were constructed to determine the associations between CVD and treatment patterns, and its impact on overall (OS) and cancer-specific survival (CSS), respectively. A competing risk multistate model was developed to determine the excess mortality risk of patients with pre-existing CVD. Results A total of 20,689 patients with lung cancer were eligible for the current analysis. Men comprised 55%, and the median age at diagnosis was 70 years. One-third had at least one CVD, with the most common being congestive heart failure in 15% of patients. Pre-existing CVD was associated with a lower likelihood of receiving chemotherapy (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.48–0.58; P < .0001), radiotherapy (OR, 0.76; 95% CI, 0.7–0.82; P < .0001), and surgery (OR, 0.56; 95% CI, 0.44–0.7; P < .0001). Adjusting for measured confounders, the presence of pre-existing CVD predicted for inferior OS (hazard ratio [HR], 1.1; 95% CI, 1.1–1.2; P < .0001) and CSS (HR, 1.1; 95% CI, 1.1–1.1; P < .0001). However, in the competing risk multistate model that adjusted for baseline characteristics, prior CVD was associated with increased risk of non-cancer related death (HR, 1.48; 95% CI, 1.33–1.64; P < 0.0001) but not cancer related death (HR, 0.98; 95% CI, 0.94–1.03; P = 0.460). Conclusions Patients with lung cancer and pre-existing CVD are less likely to receive any modality of cancer treatment and are at a higher risk of non-cancer related deaths. As effective therapies such as immuno-oncology drugs are introduced, early cardio-oncology consultation may optimize management of lung cancer

Packet-Level Adversarial Network Traffic Crafting using Sequence Generative Adversarial Networks

The surge in the internet of things (IoT) devices seriously threatens the current IoT security landscape, which requires a robust network intrusion detection system (NIDS). Despite superior detection accuracy, existing machine learning or deep learning based NIDS are vulnerable to adversarial examples. Recently, generative adversarial networks (GANs) have become a prevailing method in adversarial examples crafting. However, the nature of discrete network traffic at the packet level makes it hard for GAN to craft adversarial traffic as GAN is efficient in generating continuous data like image synthesis. Unlike previous methods that convert discrete network traffic into a grayscale image, this paper gains inspiration from SeqGAN in sequence generation with policy gradient. Based on the structure of SeqGAN, we propose Attack-GAN to generate adversarial network traffic at packet level that complies with domain constraints. Specifically, the adversarial packet generation is formulated into a sequential decision making process. In this case, each byte in a packet is regarded as a token in a sequence. The objective of the generator is to select a token to maximize its expected end reward. To bypass the detection of NIDS, the generated network traffic and benign traffic are classified by a black-box NIDS. The prediction results returned by the NIDS are fed into the discriminator to guide the update of the generator. We generate malicious adversarial traffic based on a real public available dataset with attack functionality unchanged. The experimental results validate that the generated adversarial samples are able to deceive many existing black-box NIDS

A Population-Based Study to Evaluate the Associations of Nodal Stage, Lymph Node Ratio and Log Odds of Positive Lymph Nodes with Survival in Patients with Small Bowel Adenocarcinoma

Purpose: This study aimed to determine the real-world prognostic significance of lymph node ratio (LNR) and log odds of positive lymph nodes (LOPLN) in patients with non-metastatic small bowel adenocarcinoma. Methods: Patients diagnosed with early-stage small bowel adenocarcinoma between January 2007 and December 2018 from a large Canadian province were identified. We calculated the LNR by dividing positive over total lymph nodes examined and the LOPLN as log ([positive lymph nodes + 0.5]/[negative lymph nodes + 0.5]). The LNR and LOPLN were categorized at cut-offs of 0.4 and −1.1, respectively. Multivariable Cox proportional hazards models were constructed for each nodal stage, LNR and LOPLN, adjusting for measured confounding factors. Harrell’s C-index and Akaike’s Information Criterion (AIC) were used to calculate the prognostic discriminatory abilities of the different models. Results: We identified 141 patients. The median age was 67 years and 54.6% were men. The 5-year overall survival rates for patients with stage I, II and III small bowel adenocarcinoma were 50.0%, 56.6% and 47.5%, respectively. The discriminatory ability was generally comparable for LOPLN, LNR and nodal stage in the prognostication of all patients. However, LOPLN had higher discriminatory ability among patients with at least one lymph node involvement (Harrell’s C-index, 0.75, 0.77 and 0.82, and AIC, 122.91, 119.68 and 110.69 for nodal stage, LNR and LOPLN, respectively). Conclusion: The LOPLN may provide better prognostic information when compared to LNR and nodal stage in specific patients

A Novel Graphic-Aided Algorithm (gNIPT) Improves the Accuracy of Noninvasive Prenatal Testing

Noninvasive Prenatal Testing (NIPT) has advanced the detection of fetal chromosomal aneuploidy by analyzing cell-free DNA in peripheral maternal blood. The statistic Z-test that it utilizes, which measures the deviation of each chromosome dosage from its negative control, is now widely accepted in clinical practice. However, when a chromosome has loss and gain regions which offset each other in the z-score calculation, merely using the Z-test for the result tends to be erroneous. To improve the performance of NIPT in this aspect, a novel graphic-aided algorithm (gNIPT) that requires no extra experiment procedures is reported in this study. In addition to the Z-test, this method provides a detailed analysis of each chromosome by dividing each chromosome into multiple 2 Mb size windows, calculating the z-score and copy number variation of each window, and visualizing the z-scores for each chromosome in a line chart. Data from 13537 singleton pregnancy women were analyzed and compared using both the normal NIPT (nNIPT) analysis and the gNIPT method. The gNIPT method had significantly improved the overall positive predictive value (PPV) of nNIPT (88.14% vs. 68.00%, p=0.0041) and the PPV for trisomy 21 (T21) detection (93.02% vs. 71.43%, p=0.0037). There were no significant differences between gNIPT and nNIPT in PPV for trisomy 18 (T18) detection (88.89% vs. 63.64%, p=0.1974) and in PPV for trisomy 13 (T13) detection (57.14% vs. 50.00%, p=0.8004). One false-negative T18 case in nNIPT was detected by gNIPT, which demonstrates the potency of gNIPT in discerning chromosomes that have variation in multiple regions with an offsetting effect in z-score calculation. The gNIPT was also able to detect copy number variation (CNV) in chromosomes, and one case with pathogenic CNV was detected during the study. With no additional test requirement, gNIPT presents a reasonable solution in improving the accuracy of normal NIPT

Acute Care Use by Breast Cancer Patients on Adjuvant Chemotherapy in Alberta: Demonstrating the Importance of Measurement to Improving Quality

Breast cancer patients receiving adjuvant chemotherapy are at increased risk of acute care use. The incidence of emergency department (ED) visits and hospitalizations (H) have been characterized in other provinces but never in Alberta. We conducted a retrospective population-based cohort study using administrative data of women with stage I-III breast cancer receiving adjuvant chemotherapy. Rates of ED and H use in the 180 days following chemotherapy initiation were determined, and logistic regression was performed to identify risk factors. We found that 47% of women receiving adjuvant chemotherapy experienced ED or H, which compared favourably to other provinces. However, Alberta had the highest rate of febrile neutropenia-related ED visits, and among the highest chemotherapy-related ED visits. The incidence of acute care use increased over time, and there were significant institutional differences despite operating under a single provincial healthcare system. Our study demonstrates the need for systematic measurement and the importance of quality improvement programs to address this gap