Characterization of the mechanical properties of high-moisture meat analogues using low-intensity ultrasound: Linking mechanical properties to textural and nutritional quality attributes

Plant-based meat analogues offer possible alternatives to meat consumption. However, many challenges remain to produce a palatable meat analogue as well as to understand the roles of different processing steps and ingredients on both the texture and nutritional properties of the final product. The goal of this paper is to help with addressing these challenges by using a low-intensity ultrasonic transmission technique, both online and 24 h after production, to investigate high-moisture meat analogues made from a blend of soy and wheat proteins. To understand the ultrasonic data in the context of traditional characterization methods, physical properties (meat analogue thickness, density, peak cutting force) and protein nutritional quality attributes of the meat analogues were also characterized separately. The ultrasonic velocity was found to decrease with the feed moisture content and to be strongly correlated (r = 0.97) with peak cutting force. This strong correlation extends over a wide range of moisture contents from 58% to 70%, with the velocity decreasing from about 1730 m/s to 1660 m/s over this range. The protein quality was high for all moistures, with the highest amino acid score and in vitro protein digestibility being observed for the highest moisture content treatment. The accuracy of the ultrasonic measurements was enhanced by the development of an innovative non-contact method, suitable for materials exhibiting low ultrasonic attenuation, to measure the meat analogue thickness ultrasonically and in a sanitary fashion - an advance that is potentially useful for online monitoring of production problems (e.g., extruder barrel-fill and cooling-die temperature issues). This study demonstrates, for the first time, the feasibility of using ultrasonic transmission techniques to measure both velocity and sample thickness simultaneously and provide information in real time during production that is well correlated with some textural and nutritional attributes of meat analogues.

Opportunistic CT Screening-Machine Learning Algorithm Identifies Majority of Vertebral Compression Fractures: A Cohort Study

Vertebral compression fractures (VCF) are common in patients older than 50 years but are often undiagnosed. Zebra Medical Imaging developed a VCF detection algorithm, with machine learning, to detect VCFs from CT images of the chest and/or abdomen/pelvis. In this study, we evaluated the diagnostic performance of the algorithm in identifying VCF. We conducted a blinded validation study to estimate the operating characteristics of the algorithm in identifying VCFs using previously completed CT scans from 1200 women and men aged 50 years and older at a tertiary-care center. Each scan was independently evaluated by two of three neuroradiologists to identify and grade VCF. Disagreements were resolved by a senior neuroradiologist. The algorithm evaluated the CT scans in a separate workstream. The VCF algorithm was not able to evaluate CT scans for 113 participants. Of the remaining 1087 study participants, 588 (54%) were women. Median age was 73 years (range 51-102 years; interquartile range 66-81). For the 1087 algorithm-evaluated participants, the sensitivity and specificity of the VCF algorithm in diagnosing any VCF were 0.66 (95% confidence interval [CI] 0.59-0.72) and 0.90 (95% CI 0.88-0.92), respectively, and for diagnosing moderate/severe VCF were 0.78 (95% CI 0.70-0.85) and 0.87 (95% CI 0.85-0.89), respectively. Implementing this VCF algorithm within radiology systems may help to identify patients at increased fracture risk and could support the diagnosis of osteoporosis and facilitate appropriate therapy. © 2023 Amgen, Inc. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Development and Validation of Algorithms to Identify COVID-19 Patients Using a US Electronic Health Records Database: A Retrospective Cohort Study

Introduction

In order to identify and evaluate candidate algorithms to detect COVID-19 cases in an electronic health record (EHR) database, this study examined and compared the utilization of acute respiratory disease codes from February to August 2020 versus the corresponding time period in the 3 years preceding.

Methods

De-identified EHR data were used to identify codes of interest for candidate algorithms to identify COVID-19 patients. The number and proportion of patients who received a SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) within ±10 days of the occurrence of the diagnosis code and patients who tested positive among those with a test result were calculated, resulting in 11 candidate algorithms. Sensitivity, specificity, and likelihood ratios assessed the candidate algorithms by clinical setting and time period. We adjusted for potential verification bias by weighting by the reciprocal of the estimated probability of verification.

Results

From January to March 2020, the most commonly used diagnosis codes related to COVID-19 diagnosis were R06 (dyspnea) and R05 (cough). On or after April 1, 2020, the code with highest sensitivity for COVID-19, U07.1, had near perfect adjusted sensitivity (1.00 [95% CI 1.00, 1.00]) but low adjusted specificity (0.32 [95% CI 0.31, 0.33]) in hospitalized patients.

Discussion

Algorithms based on the U07.1 code had high sensitivity among hospitalized patients, but low specificity, especially after April 2020. None of the combinations of ICD-10-CM codes assessed performed with a satisfactory combination of high sensitivity and high specificity when using the SARS-CoV-2 RT-PCR as the reference standard.

Coronary artery calcium scores indicating secondary prevention level risk: Findings from the CAC consortium and FOURIER trial

BACKGROUND AND AIMS

Coronary artery calcium (CAC) burden displays a stepwise association with atherosclerotic cardiovascular disease (ASCVD) risk. Among primary prevention patients, we sought to determine the CAC scores equivalent to ASCVD mortality rates observed in the FOURIER trial, a modern secondary prevention cohort.

METHODS AND RESULTS

For the main analysis, we included participants from the CAC Consortium ≥50 years old with a 10-year ASCVD risk ≥7.5% (n = 20,207). Poisson regression was used to define the relationship between CAC and annual ASCVD mortality. Equations generated from the regression models were then used to derive CAC scores associated with equivalent annual ASCVD mortality as observed in FOURIER placebo participants from the overall trial and in key trial subgroups. The CAC Consortium participants had a similar age (65.5 versus 62.5 years) and sex (22% versus 24% female) distribution as FOURIER. The annualized ASCVD mortality rate in FOURIER participants (0.766 per 100 person-years) corresponded to a CAC score of 781 (418-1467). A CAC score of 255 (162-394) corresponded to an ASCVD mortality rate equivalent to the lowest risk FOURIER subgroup (presence of myocardial infarction >2 years prior to trial enrollment). No CAC score produced a risk equivalent to high-risk FOURIER subgroups, particularly those with symptomatic peripheral arterial disease and/or multivessel coronary heart disease.

CONCLUSIONS

Primary prevention individuals with increased CAC burden may have annualized ASCVD mortality rates equivalent to persons with stable secondary prevention-level risk. These findings argue for a risk continuum between higher risk primary prevention and stable secondary prevention patients, as their ASCVD risks may overlap.

Trends in characteristics and outcomes among US adults hospitalised with COVID-19 throughout 2020: an observational cohort study

OBJECTIVES

To examine the temporal patterns of patient characteristics, treatments used and outcomes associated with COVID-19 in patients who were hospitalised for the disease between January and 15 November 2020.

DESIGN

Observational cohort study.

SETTING

COVID-19 subset of the Optum deidentified electronic health records, including more than 1.8 million patients from across the USA.

PARTICIPANTS

There were 51 510 hospitalised patients who met the COVID-19 definition, with 37 617 in the laboratory positive cohort and 13 893 in the clinical cohort.

PRIMARY AND SECONDARY OUTCOME MEASURES

Incident acute clinical outcomes, including in-hospital all-cause mortality.

RESULTS

Respectively, 48% and 49% of the laboratory positive and clinical cohorts were women. The 50- 65 age group was the median age group for both cohorts. The use of antivirals and dexamethasone increased over time, fivefold and twofold, respectively, while the use of hydroxychloroquine declined by 98%. Among adult patients in the laboratory positive cohort, absolute age/sex standardised incidence proportion for in-hospital death changed by -0.036 per month (95% CI -0.042 to -0.031) from March to June 2020, but remained fairly flat from June to November, 2020 (0.001 (95% CI -0.001 to 0.003), 17.5% (660 deaths /3986 persons) in March and 10.2% (580/5137) in October); in the clinical cohort, the corresponding changes were -0.024 (95% CI -0.032 to -0.015) and 0.011 (95% CI 0.007 0.014), respectively (14.8% (175/1252) in March, 15.3% (189/1203) in October). Declines in the cumulative incidence of most acute clinical outcomes were observed in the laboratory positive cohort, but not for the clinical cohort.

CONCLUSION

The incidence of adverse clinical outcomes remains high among COVID-19 patients with clinical diagnosis only. Patients with COVID-19 entering the hospital are at elevated risk of adverse outcomes.

The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study

BACKGROUND

The current COVID-19 pandemic is unprecedented; under resource-constrained settings, predictive algorithms can help to stratify disease severity, alerting physicians of high-risk patients; however, there are only few risk scores derived from a substantially large electronic health record (EHR) data set, using simplified predictors as input.

OBJECTIVE

The objectives of this study were to develop and validate simplified machine learning algorithms that predict COVID-19 adverse outcomes; to evaluate the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and calibration of the algorithms; and to derive clinically meaningful thresholds.

METHODS

We performed machine learning model development and validation via a cohort study using multicenter, patient-level, longitudinal EHRs from the Optum COVID-19 database that provides anonymized, longitudinal EHR from across the United States. The models were developed based on clinical characteristics to predict 28-day in-hospital mortality, intensive care unit (ICU) admission, respiratory failure, and mechanical ventilator usages at inpatient setting. Data from patients who were admitted from February 1, 2020, to September 7, 2020, were randomly sampled into development, validation, and test data sets; data collected from September 7, 2020, to November 15, 2020, were reserved as the postdevelopment prospective test data set.

RESULTS

Of the 3.7 million patients in the analysis, 585,867 patients were diagnosed or tested positive for SARS-CoV-2, and 50,703 adult patients were hospitalized with COVID-19 between February 1 and November 15, 2020. Among the study cohort (n=50,703), there were 6204 deaths, 9564 ICU admissions, 6478 mechanically ventilated or EMCO patients, and 25,169 patients developed acute respiratory distress syndrome or respiratory failure within 28 days since hospital admission. The algorithms demonstrated high accuracy (AUC 0.89, 95% CI 0.89-0.89 on the test data set [n=10,752]), consistent prediction through the second wave of the pandemic from September to November (AUC 0.85, 95% CI 0.85-0.86) on the postdevelopment prospective test data set [n=14,863], great clinical relevance, and utility. Besides, a comprehensive set of 386 input covariates from baseline or at admission were included in the analysis; the end-to-end pipeline automates feature selection and model development. The parsimonious model with only 10 input predictors produced comparably accurate predictions; these 10 predictors (age, blood urea nitrogen, SpO₂, systolic and diastolic blood pressures, respiration rate, pulse, temperature, albumin, and major cognitive disorder excluding stroke) are commonly measured and concordant with recognized risk factors for COVID-19.

CONCLUSIONS

The systematic approach and rigorous validation demonstrate consistent model performance to predict even beyond the period of data collection, with satisfactory discriminatory power and great clinical utility. Overall, the study offers an accurate, validated, and reliable prediction model based on only 10 clinical features as a prognostic tool to stratifying patients with COVID-19 into intermediate-, high-, and very high-risk groups. This simple predictive tool is shared with a wider health care community, to enable service as an early warning system to alert physicians of possible high-risk patients, or as a resource triaging tool to optimize health care resources.

Derivation of a Coronary Age Calculator Using Traditional Risk Factors and Coronary Artery Calcium: The Multi-Ethnic Study of Atherosclerosis

Background

The optimal method for communicating coronary heart disease (CHD) risk to individual patients is not yet clear. Recent research supports the concept of "coronary age" for more effective risk communication. We defined an individual's coronary age as the age at which an average healthy individual would have an equivalent estimated CHD risk as that calculated for the index individual, building on our previously validated MESA (Multi‐Ethnic Study of Atherosclerosis) 10‐year CHD Risk Score equations with and without coronary artery calcium (CAC).

Methods and Results

We derived a coronary age by (1) calculating the MESA 10‐year CHD risk; (2) mathematically setting this equal to an equation describing risk of an average healthy MESA participant, as a function of age; and (3) solving for age. The risk discrimination of the resultant coronary age was compared with that of chronological age, the MESA CHD Risk Score, and CAC alone. Approximately 95% of coronary age values ranged from 30 years less to 30 years higher than chronological age. Although the mean chronological age of individuals experiencing CHD events compared with those free of events was 67.4 versus 61.8 years, the difference in coronary age including CAC was larger (80.6 versus 62.8 years). Coronary age with CAC had identical predictive ability to that of MESA CHD Risk Score and outperformed chronological age and CAC alone.

Conclusions

The newly derived coronary age is a convenient transformation of MESA CHD Risk, retaining very good risk discrimination. This easy‐to‐communicate tool will be available for patients and clinicians, potentially facilitating risk communication in routine care.

A PDMS-based broadband acoustic impedance matched material for underwater applications

Having a material that is matched in acoustic impedance with the surrounding medium is a considerable asset for many underwater acoustic applications. In this work, impedance matching is achieved by dispersing small, deeply subwavelength sized particles in a soft matrix, and the appropriate concentration is determined with the help of Coherent Potential Approximation and Waterman & Truell models. We show experimentally the validity of the models using mixtures of Polydimethylsiloxane (PDMS) and TiO₂ particles. The optimized composite material has the same longitudinal acoustic impedance as water and therefore the acoustic reflection coefficient is essentially zero over a wide range of frequencies (0.5-6 MHz). PDMS-based materials can be cured in a mold to achieve desired sample shape, which makes them very easy to handle and to use. Various applications can be envisioned, such the use of impedance-matched PDMS in the design and fabrication of acoustically transparent cells for samples, perfectly matched layers for ultrasonic experiments, or superabsorbing metamaterials for water-borne acoustic waves.

Value of incorporating newly identified risk factors into risk prediction for chemotherapy-induced febrile neutropenia

Several comorbidities have recently been shown to affect risk of chemotherapy-induced febrile neutropenia (FN). Here, we evaluated the added predictive value of these comorbidities beyond established FN risk factors. A retrospective cohort study was conducted among adult patients diagnosed with cancer and treated with chemotherapy at Kaiser Permanente Southern California between 2000 and 2009. The study cohort was equally split into training and validation datasets to develop and evaluate the performance of FN risk prediction models in the first chemotherapy cycle. A reference model was developed based on the model proposed by Lyman et al (Cancer 2011;117:1917). A new model was developed by incorporating the newly identified comorbidities such as rheumatoid conditions and thyroid disorders into the reference model. Area under the receiver operating characteristic curve (AUROCC), risk reclassification, and integrated discrimination improvement (IDI) were used to evaluate the potential improvement of FN risk prediction by incorporating comorbidities. A total of 15 279 patients were included; 4.2% experienced FN in the first chemotherapy cycle. Including comorbidities in FN risk prediction did not improve AUROCC (reference model 0.71 vs new model 0.72). A significant improvement in individual-level FN risk prediction was indicated by IDI (P = .02). However, significant improvement in risk reclassification was not observed overall (although 6% of all patients were more accurately classified for their FN risk level, 5% were less accurately classified) or when examining predicted FN risk among patients who did and did not develop FN. Incorporating several new comorbidities into FN prediction led to improved FN risk prediction in the first chemotherapy cycle, although the observed improvements were small and might not be clinically relevant.

Impact of Strong Scattering Resonances on Ballistic and Diffusive Wave Transport

The strong impact of scattering resonances on all the key transport parameters of classical waves in disordered media is demonstrated through ultrasonic experiments on monodisperse emulsions. Through accurate measurements of both ballistic and diffusive transport over a wide range of frequencies, we show that the group velocity is large near sharp resonances, whereas the energy velocity (as well as the diffusion coefficient) is significantly slowed down by resonant scattering delay. Excellent agreement between theory and experiment is found, elucidating the effects of resonant scattering on wave transport in both acoustics and optics.

Relation between ultrasonic properties, rheology and baking quality for bread doughs of widely differing formulation

BACKGROUND

The objective was to evaluate whether an ultrasonic reflectance technique has predictive capacity for breadmaking performance of doughs made under a wide range of formulation conditions. Two flours of contrasting dough strength augmented with different levels of ingredients (inulin, oil, emulsifier or salt) were used to produce different bread doughs with a wide range of properties. Breadmaking performance was evaluated by conventional large-strain rheological tests on the dough and by assessment of loaf quality. The ultrasound tests were performed with a broadband reflectance technique in the frequency range of 0.3-6 MHz.

RESULTS

Principal component analysis showed that ultrasonic attenuation and phase velocity at frequencies between 0.3 and 3 MHz are good predictors for rheological and bread scoring characteristics.

CONCLUSIONS

Ultrasonic parameters had predictive capacity for breadmaking performance for a wide range of dough formulations. Lower frequency attenuation coefficients correlated well with conventional quality indices of both the dough and the bread. © 2016 Society of Chemical Industry.

Dynamic sound scattering: Field fluctuation spectroscopy with singly scattered ultrasound in the near and far fields

Dynamic sound scattering (DSS) is a powerful acoustic technique for investigating the motion of particles or other inclusions inside an evolving medium. In DSS, this dynamic information is obtained by measuring the field autocorrelation function of the temporal fluctuations of singly scattered acoustic waves. The technique was initially introduced 15 years ago, but its technical aspects were not adequately discussed then. This paper addresses the need for a more complete account of the method by describing in detail two different implementations of this sound scattering technique, one of which is specifically adapted to a common experimental situation in ultrasonics. The technique is illustrated by the application of DSS to measure the mean square velocity fluctuations of particles in fluidized suspensions, as well as the dynamic velocity correlation length. By explaining the experimental and analytical methods involved in realizing the DSS technique in practice, the use of DSS will be facilitated for future studies of particulate suspension dynamics and particle properties over a wide range of particle sizes and concentrations, from millimeters down to nanometers, where the use of optical techniques is often limited by the opacity of the medium.

Anderson Mobility Gap Probed by Dynamic Coherent Backscattering

We use dynamic coherent backscattering to study one of the Anderson mobility gaps in the vibrational spectrum of strongly disordered three-dimensional mesoglasses. Comparison of experimental results with the self-consistent theory of localization allows us to estimate the localization (correlation) length as a function of frequency in a wide spectral range covering bands of diffuse transport and a mobility gap delimited by two mobility edges. The results are corroborated by transmission measurements on one of our samples.

Incidence of anemia in patients diagnosed with solid tumors receiving chemotherapy, 2010-2013

Purpose

The purpose of this study was to evaluate and characterize the risk of anemia during the course of chemotherapy among patients with five common types of solid tumors.

Patients and methods

Patients diagnosed with incident cancers of breast, lung, colon/rectum, stomach, and ovary who received chemotherapy were identified from Kaiser Permanente Southern California Health Plan (2010–2012). All clinical data were collected from the health plan’s electronic medical records. Incidence proportions of patients developing anemia and 95% confidence intervals were calculated overall and by anemia severity and type, as well as by stage at cancer diagnosis, and by chemotherapy regimen and cycle.

Results

A total of 4,426 patients who received chemotherapy were included. Across cancers, 3,962 (89.5%) patients developed anemia during the course of chemotherapy (normocytic 85%, macrocytic 10%, microcytic 5%; normochromic 47%, hyperchromic 44%, hypochromic 9%). The anemia grades were distributed as follows: 58% were grade 1, 34% grade 2, 8% grade 3, and <1% grade 4. The incidence of grade 2+ anemia ranged from 26.3% in colorectal cancer patients to 59.2% in ovarian cancer patients. Incidence of grade 2+ anemia increased from 29% in stage I to 49% in stage IV. Incidence of grade 2+ anemia varied from 18.2% in breast cancer patients treated with cyclophosphamide + docetaxel regimen to 59.7% in patients with ovarian cancer receiving carboplatin + paclitaxel regimen.

Conclusion

The incidence of moderate-to-severe anemia (hemoglobin <10 g/dL) remained considerably high in patients with solid tumors receiving chemotherapy. The risk of anemia was greater in patients with distant metastasis.

Trajectory of absolute neutrophil counts in patients treated with pegfilgrastim on the day of chemotherapy versus the day after chemotherapy

PURPOSE

Risk of infection increases with severity and duration of chemotherapy-induced neutropenia (CIN). Pegfilgrastim is approved for use on the day after chemotherapy to reduce incidence of infection, as manifested by febrile neutropenia (FN), in patients receiving myelosuppressive chemotherapy. In this study, we compared severity and duration of absolute neutrophil count (ANC) suppression in patients who received pegfilgrastim on the same day as chemotherapy versus the next day.

METHODS

We combined individual patient data from four Amgen-sponsored clinical trials in which patients with cancer were randomized to receive pegfilgrastim either the same day as chemotherapy or the next day. Severity and duration of ANC suppression were calculated using area over the curve (AOC, the area over the ANC-time response curve and below a given clinical threshold). AOC of ANC and incidences of CIN and FN were compared by day of pegfilgrastim use.

RESULTS

The analysis included 95 same-day patients and 97 next-day patients. Despite similar ANC at baseline, ANC at nadir was higher among next-day patients than same-day patients. Mean AOC of ANC (cutoff 0.5 × 10(9)/L) among next-day patients was lower by 0.30 (95 % confidence interval: 0.16, 0.43) 10(9)/L × day than same-day patients in cycle 1. Next-day patients had lower incidences of CIN than same-day patients, but there were no significant differences in incidences of FN.

CONCLUSIONS

Patients who received pegfilgrastim the day after chemotherapy had less severe and shorter suppression of ANC than patients who received pegfilgrastim the same day as chemotherapy.

Abstract P1-10-04: A prospective study of patterns of chemotherapy, colony-stimulating factor use, and burden of colony-stimulating factor injections in patients with early-stage breast cancer

Background: Febrile neutropenia (FN) is a common side effect of myelosuppressive chemotherapy. Primary prophylaxis with colony-stimulating factors (CSFs) can reduce FN incidence and is recommended when a patient has a high risk of FN (&gt; 20%). In the prophylactic setting, CSFs should be administered at least 24 hours after chemotherapy completion. Patient burden associated with CSF administration is not well understood. Here we describe current patterns of chemotherapy use and burden of CSF injections for patients with early-stage breast cancer (ESBC) in US clinical practice.

Methods: This was a prospective cohort study of adult ESBC patients receiving their first chemotherapy course who had a high risk of FN based on high- or intermediate-risk chemotherapy regimen and individual FN risk factors. The burden associated with CSF injections was assessed via questionnaires among patients who received CSF, and a subset analysis of patient burden in the first cycle of chemotherapy is reported.

Results: 598 patients completed the "burden of CSF injections" questionnaire following the first cycle of chemotherapy. Most patients were &lt; 65 years old (76.8%), had a BMI &lt; 30 kg/m2 (54.9%), and had few comorbidities (see table for additional characteristics and comorbidities). The three most common chemotherapy regimens received were ddAC-T (34.4%), TC (23.4%), and TCH (15.6%). 98.3% of patients received prophylaxis with CSF in the first chemotherapy cycle: 94.6% of these received pegfilgrastim, and 5.4% received filgrastim. Among all patients who received CSF, mean (SD) one-way travel time for a single CSF injection was 31 (25) minutes; mean (SD) time in office to receive a CSF injection was 41 (68) minutes. Across the first chemotherapy cycle, mean (SD) time missed from work for CSF administration was 3.1 (9.3) hours, and mean (SD) time missed from non-work activities was 5.5 (14.4) hours. 66.3% of patients had someone else assist them with travel to the clinic to receive CSF, of which 98.8% were helped by an unpaid caregiver. When patients were questioned about the subjective burden of CSF injections, 25.4% reported some degree of bother, and 15.9% reported at least moderate inconvenience.

Conclusions: Among the high- and intermediate-risk regimens investigated here, dose-dense and taxane-based chemotherapy regimens were common. As many high-risk patients with ESBC receive primary prophylaxis with CSF, travel and time needed to receive CSF can contribute to patient and caregiver burden.

Patient CharacteristicsN = 598 Age, mean (SD) years55.1 (11.3) BMI, mean (SD) kg/m230.7 (7.5) HER2+23.2% Luminal Aa52.0% Triple negative21.6% Stage at diagnosis  124.6% 253.7% 321.2% Missing0.5%Comorbidities &gt; 10% Hypertension37.5% Hyperlipidemia24.7% Depression13.9% Diabetes mellitus13.4% Osteoarthritis12.7% Gastroesophageal reflux disease12.2% Hypothyroidism12.0% Anxiety11.9%aHormone receptor positive but HER2 negative.

Citation Format: Li X, Barron R, Tzivelekis S, Li Y, Chandler D, Xu H, Morrow PK, Klippel Z, Nagarajan A, Reiner M, Page JH. A prospective study of patterns of chemotherapy, colony-stimulating factor use, and burden of colony-stimulating factor injections in patients with early-stage breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-10-04.

Validation of Claims Algorithms for Progression to Metastatic Cancer in Patients with Breast, Non-small Cell Lung, and Colorectal Cancer

Background

Validated algorithms for identifying progression to metastatic cancer could permit the use of administrative claims databases for research in this area.

Objective

To identify simple algorithms that could accurately detect cancer progression to metastatic breast, non-small cell lung, and colorectal cancer (CRC) using medical and pharmacy claims data.

Methods

Adults with stage I–III breast, non-small cell lung cancer (NSCLC), or CRC in the Geisinger Health System from 2004 to 2011 were selected. Evidence of progression was extracted via manual chart review as the reference standard. In addition to secondary malignancy diagnosis (ICD-9 code for metastases), diagnoses, procedures, and treatments were selected with clinician input as indicators of cancer progression. Random forests models provided variable importance scores. In addition to codes for secondary malignancy, several more complex algorithms were constructed and performance measures calculated.

Results

Among those with breast cancer [17/502 (3.4%) progressed], the performance of a secondary malignancy code was suboptimal [sensitivity: 64.7%; specificity: 86.0%; positive predictive value (PPV): 13.9; negative predictive value (NPV): 98.6%]; requiring malignancy at another site or initiation of immunotherapy increased PPV and specificity but decreased sensitivity. For NSCLC [61/236 (25.8%) progressed], codes for secondary malignancy alone (PPV: 47.4%; NPV: 84.8%; sensitivity: 60.7%; specificity: 76.6%) performed similarly or better than more complex algorithms. For CRC [33/276 (12.0%) progressed], secondary malignancy codes had good specificity (92.7%) and NPV (92.3%) but low sensitivity (42.4%) and PPV (43.8%); an algorithm with change in chemotherapy increased sensitivity but decreased other metrics.

Conclusion

Selected algorithms performed similarly to the presence of a secondary tumor diagnosis code, with low sensitivity/PPV and higher specificity/NPV. Accurate identification of cancer progression likely requires verification through chart review.

The impact of primary prophylaxis with granulocyte colony-stimulating factors on febrile neutropenia during chemotherapy: a systematic review and meta-analysis of randomized controlled trials

PURPOSE

The study aims to assess the relative efficacy of granulocyte colony-stimulating factor (G-CSF) products administered as primary prophylaxis (PP) to patients with cancer receiving myelosuppressive chemotherapy.

METHODS

A systematic literature review identified publications (January 1990 to September 2013) of randomized controlled trials evaluating PP with filgrastim, pegfilgrastim, lenograstim, or lipegfilgrastim in adults receiving myelosuppressive chemotherapy for solid tumors or non-Hodgkin lymphoma. Direct, indirect, and mixed-treatment comparison (MTC) were used to estimate the odds ratio and 95 % credible interval of febrile neutropenia (FN) during cycle 1 and all cycles of chemotherapy combined without adjusting for differences in relative dose intensity (RDI) between study treatment arms.

RESULTS

Twenty-seven publications representing 30 randomized controlled trials were included. Using MTC over all chemotherapy cycles, PP with filgrastim, pegfilgrastim, lenograstim, and lipegfilgrastim versus no G-CSF PP or placebo were associated with statistically significantly reduced FN risk. FN risk was also significantly reduced with pegfilgrastim PP versus filgrastim PP. Over all chemotherapy cycles, there was a numerical but statistically nonsignificant increase in the FN risk for lipegfilgrastim PP versus pegfilgrastim PP. Using MTC in cycle 1, PP with filgrastim, pegfilgrastim, and lipegfilgrastim versus no G-CSF PP or placebo were associated with statistically significantly reduced FN risk.

CONCLUSIONS

In this meta-analysis, using MTC without adjustment for RDI, PP with all G-CSFs evaluated reduced the FN risk in patients receiving myelosuppressive chemotherapy. Future studies are needed to assess the influence of RDI on FN outcomes and to eliminate potential bias between G-CSF arms receiving more intensive chemotherapy than control arms.

Polymorphisms of an innate immune gene, toll-like receptor 4, and aggressive prostate cancer risk: a systematic review and meta-analysis

BACKGROUND

Toll-like receptor 4 (TLR4) is one of the best known TLR members expressed on the surface of several leukocytes and tissue cells and has a key function in detecting pathogen and danger-associated molecular patterns. The role of TLR4 in the pathophysiology of several age-related diseases is also well recognized, such as prostate cancer (PCa). TLR4 polymorphisms have been related to PCa risk, but the relationship between TLR4 genotypes and aggressive PCa risk has not been evaluated by any systematic reviews.

METHODS

We performed a systematic review and meta-analysis of candidate-gene and genome-wide association studies analyzing this relationship and included only white population. Considering appropriate criteria, only nine studies were analyzed in the meta-analysis, including 3,937 aggressive PCa and 7,382 controls.

RESULTS

Using random effects model, no significant association was found in the ten TLR4 SNPs reported by at least four included studies under any inheritance model (rs2737191, rs1927914, rs10759932, rs1927911, rs11536879, rs2149356, rs4986790, rs11536889, rs7873784, and rs1554973). Pooled estimates from another ten TLR4 SNPs reported by three studies also showed no significant association (rs10759930, rs10116253, rs11536869, rs5030717, rs4986791, rs11536897, rs1927906, rs913930, rs1927905, and rs7045953). Meta-regression revealed that study type was not a significant source of between-study heterogeneity.

CONCLUSIONS

TLR4 polymorphisms were not significantly associated with the risk of aggressive PCa.

History of chronic comorbidity and risk of chemotherapy-induced febrile neutropenia in cancer patients not receiving G-CSF prophylaxis

BACKGROUND

Chemotherapy-induced febrile neutropenia (FN) is a clinically important complication that affects patient outcome by delaying chemotherapy doses or reducing dose intensity. Risk of FN depends on chemotherapy- and patient-level factors. We sought to determine the effects of chronic comorbidities on risk of FN.

DESIGN

We conducted a cohort study to examine the association between a variety of chronic comorbidities and risk of FN in patients diagnosed with six types of cancer (non-Hodgkin lymphoma and breast, colorectal, lung, ovary, and gastric cancer) from 2000 to 2009 who were treated with chemotherapy at Kaiser Permanente Southern California, a large managed care organization. We excluded those patients who received primary prophylactic granulocyte colony-stimulating factor. History of comorbidities and FN events were identified using electronic medical records. Cox models adjusting for propensity score, stratified by cancer type, were used to determine the association between comorbid conditions and FN. Models that additionally adjusted for cancer stage, baseline neutrophil count, chemotherapy regimen, and dose reduction were also evaluated.

RESULTS

A total of 19 160 patients with mean age of 60 years were included; 963 (5.0%) developed FN in the first chemotherapy cycle. Chronic obstructive pulmonary disease [hazard ratio (HR) = 1.30 (1.07-1.57)], congestive heart failure [HR = 1.43 (1.00-1.98)], HIV infection [HR = 3.40 (1.90-5.63)], autoimmune disease [HR = 2.01 (1.10-3.33)], peptic ulcer disease [HR = 1.57 (1.05-2.26)], renal disease [HR = 1.60 (1.21-2.09)], and thyroid disorder [HR = 1.32 (1.06-1.64)] were all associated with a significantly increased FN risk.

CONCLUSIONS

These results provide evidence that history of several chronic comorbidities increases risk of FN, which should be considered when managing patients during chemotherapy.

History of chronic comorbidity and risk of chemotherapy-induced febrile neutropenia in patients with non-Hodgkin lymphoma not receiving granulocyte colony-stimulating factor prophylaxis

We conducted a cohort study to examine the association between a wide variety of chronic comorbidities and risk of febrile neutropenia (FN) in patients with non-Hodgkin lymphoma (NHL) from 2000 to 2009 treated with chemotherapy at Kaiser Permanente Southern California. History of comorbidities and FN events were identified using electronic medical records. Cox model adjusting for propensity score was used to determine the association between a comorbid condition and FN. Models that additionally adjusted for cancer stage, baseline absolute neutrophil count, chemotherapy regimen and dose reduction were also evaluated. A total of 2480 patients with NHL were included, and 60% received CHOP/R-CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone, with or without rituximab). In total, 236 (9.5%) patients developed FN in the first chemotherapy cycle. Anemia (adjusted hazard ratio [HR] = 1.6, 95% confidence interval [1.2-2.2]), HIV infection (HR = 3.8 [2.0-6.7]) and rheumatoid diseases (HR = 2.4 [1.3-4.0]) were associated with significantly increased risk of FN. These results provide evidence that chronic comorbidity increases the risk of FN.

Use of pegfilgrastim primary prophylaxis and risk of infection, by chemotherapy cycle and regimen, among patients with breast cancer or non-Hodgkin's lymphoma

PURPOSE

This study aims to examine granulocyte colony-stimulating factor (G-CSF) prophylaxis by cancer type, chemotherapy regimen, and cycle in a real-world setting to assess if practice conforms to clinical guidelines, which recommend G-CSF prophylaxis every cycle when a patient's risk of febrile neutropenia (FN) is 20% or greater, and to describe the incidence of FN among patients who discontinue pegfilgrastim (peg) prophylaxis.

METHODS

The cohort was selected from administrative claims data and includes adults diagnosed with non-Hodgkin's lymphoma (NHL) or breast cancer (BC) who began chemotherapy 2005-2010.

RESULTS

About 83.2% of the 4,470 patients with BC treated with dose-dense doxorubicin, cyclophosphamide (ddAC), 83.6% of 2,197 patients with BC treated with docetaxel, doxorubicin, cyclophosphamide (TAC), and about 55.6% of the 2,722 patients with NHL treated with cyclophosphamide, doxorubicin, vincristine, with or without prednisone for 3-week cycles (CHOP-R Q3W) received peg prophylaxis in cycle 1. Among patients on these regimens who received peg prophylaxis in cycle 1 and were still on the regimen in cycle 4, about 90% received peg prophylaxis in that cycle. Among patients with BC or NHL who discontinued G-CSF, the incidence proportion of infection or FN varied by regimen and cycle, with a range from 0 to 14%.

CONCLUSIONS

Despite clinical guidelines recommending G-CSF prophylaxis with chemotherapy regimens with a high risk of FN, many NHL and BC patients do not receive FN prophylaxis in cycle 1. However, among patients who receive G-CSF in cycle 1 and remain on the regimen, the majority appear to continue prophylaxis as indicated.

Observation of infinite-range intensity correlations above, at, and below the mobility edges of the 3D Anderson localization transition

We investigate long-range intensity correlations on both sides of the Anderson transition of classical waves in a three-dimensional disordered material. Our ultrasonic experiments are designed to unambiguously detect a recently predicted infinite-range C0 contribution, due to local density of states fluctuations near the source. We find that these C0 correlations, in addition to C2 and C3 contributions, are significantly enhanced near mobility edges. Separate measurements of the inverse participation ratio reveal a link between C0 and the anomalous dimension Δ2, implying that C0 may also be used to explore the critical regime of the Anderson transition.

Granulocyte colony-stimulating factor (G-CSF) patterns of use in cancer patients receiving myelosuppressive chemotherapy

PURPOSE

Febrile neutropenia (FN) is a common and serious complication of myelosuppressive chemotherapy. Guidelines recommend primary granulocyte colony-stimulating factors (G-CSF) prophylaxis (PPG) in patients with a high risk (HR, >20 %) of developing FN. We performed a retrospective analysis using a subset of the Medicare 5 % database to assess patterns of G-CSF use and FN occurrence among elderly cancer patients receiving myelosuppressive chemotherapy.

METHODS

Chemotherapy courses for patients aged 65+ years were identified; only the first course was used for this analysis. Using clinical guidelines, chemotherapy regimens were classified as HR or intermediate risk (IR) for FN. The first administration of G-CSF was classified as either PPG (within the first 5 days of the first cycle), secondary prophylaxis, or reactive.

RESULTS

Twelve thousand seven hundred seven courses across five tumor types were classified as having a HR or IR regimen. G-CSF was used in 24.5-73.8 % of patients receiving a HR FN regimen, with the highest use in breast cancer or NHL. Except for breast cancer (where PPG was used in 52.1 %), PPG was given in less than half of patients receiving a HR regimen. Depending on the tumor type, 4.8-22.6 % of patients with a HR regimen had a neutropenia-related hospitalization.

CONCLUSIONS

Guidelines recommend PPG with HR FN regimens and older age (>65 years), an important risk factor for developing severe neutropenic complications. However, our results show that in this elderly population, PPG was not routinely used (range 4.8-52.1 %) in patients receiving HR FN regimens. Careful attention to FN risk factors, including chemotherapy regimen and patient age, is needed when planning treatment strategies.

Recurrent scattering and memory effect at the Anderson localization transition

We report on ultrasonic measurements of the propagation operator in a strongly scattering mesoglass. The backscattered field is shown to display a deterministic spatial coherence due to a remarkably large memory effect induced by long recurrent trajectories. Investigation of the recurrent scattering contribution directly yields the probability for a wave to come back close to its starting spot. The decay of this quantity with time is shown to change dramatically near the Anderson localization transition. The singular value decomposition of the propagation operator reveals the dominance of very intense recurrent scattering paths near the mobility edge.

Chronic comorbid conditions associated with risk of febrile neutropenia in breast cancer patients treated with chemotherapy

Chemotherapy-induced febrile neutropenia (FN) is associated with increased patient mortality and health care costs. Comorbid conditions such as liver and renal dysfunction have been linked to increased risk of FN. However, the effects of other chronic comorbid conditions on risk of FN have not been well studied. To examine the association between chronic comorbid conditions and FN in breast cancer patients, we identified incident breast cancer patients from 2000 to 2009 treated with chemotherapy at Kaiser Permanente Southern California, a large managed care organization. Patients who received primary prophylactic granulocyte colony-stimulating factor (G-CSF) were excluded. We assessed history of comorbid conditions prior to cancer diagnosis using ICD-9 codes and disease registries. FN events were identified in the first chemotherapy cycle using a combination of ICD-9 codes and hospital discharge diagnoses. For each comorbid condition, propensity scores that included patient characteristics and other predisposing comorbid conditions were calculated and adjusted for in Cox models to determine associations between that comorbid condition and FN. We also evaluated secondary models that additionally adjusted for cancer stage, baseline absolute neutrophil count (ANC), chemotherapy regimen, and dose reductions. A total of 7,127 breast cancer patients were included; median age was 55 years, and the majority had localized (47 %) or regional (49 %) disease at diagnosis. In the first chemotherapy cycle, 335 (4.7 %) patients developed FN. Congestive heart failure (HR = 3.0; 95 % CI: 1.3-5.9), osteoarthritis (HR = 2.0; 95 % CI: 1.4-2.8), previous cancer (HR = 3.4; 95 % CI: 1.2-7.5), and thyroid disorder (HR = 1.6; 95 % CI: 1.1-2.3) were associated with increased risk of FN. These estimates were similar to those from secondary models that also adjusted for additional cancer and treatment-related covariates. Our findings suggest that several chronic comorbid conditions may be associated with risk of FN. This information, if confirmed by others, may aid clinical decision making with respect to use of prophylactic G-CSF during chemotherapy treatment.

Structural Nested Cumulative Failure Time Models to Estimate the Effects of Interventions

In the presence of time-varying confounders affected by prior treatment, standard statistical methods for failure time analysis may be biased. Methods that correctly adjust for this type of covariate include the parametric g-formula, inverse probability weighted estimation of marginal structural Cox proportional hazards models, and g-estimation of structural nested accelerated failure time models. In this article, we propose a novel method to estimate the causal effect of a time-dependent treatment on failure in the presence of informative right-censoring and time-dependent confounders that may be affected by past treatment: g-estimation of structural nested cumulative failure time models (SNCFTMs). An SNCFTM considers the conditional effect of a final treatment at time m on the outcome at each later time k by modeling the ratio of two counterfactual cumulative risks at time k under treatment regimes that differ only at time m. Inverse probability weights are used to adjust for informative censoring. We also present a procedure that, under certain "no-interaction" conditions, uses the g-estimates of the model parameters to calculate unconditional cumulative risks under nondynamic (static) treatment regimes. The procedure is illustrated with an example using data from a longitudinal cohort study, in which the "treatments" are healthy behaviors and the outcome is coronary heart disease.

Influence of positional correlations on the propagation of waves in a complex medium with polydisperse resonant scatterers

We present experimental results on a model system for studying wave propagation in a complex medium exhibiting low-frequency resonances. These experiments enable us to investigate a fundamental question that is relevant for many materials, such as metamaterials, where low-frequency scattering resonances strongly influence the effective medium properties. This question concerns the effect of correlations in the positions of the scatterers on the coupling between their resonances, and hence on wave transport through the medium. To examine this question experimentally, we measure the effective medium wavenumber of acoustic waves in a sample made of bubbles embedded in an elastic matrix over a frequency range that includes the resonance frequency of the bubbles. The effective medium is highly dispersive, showing peaks in the attenuation and the phase velocity as functions of the frequency, which cannot be accurately described using the independent scattering approximation (ISA). This discrepancy may be explained by the effects of the positional correlations of the scatterers, which we show to be dependent on the size of the scatterers. We propose a self-consistent approach for taking this "polydisperse correlation" into account and show that our model better describes the experimental results than the ISA.

A statistical approach to direct density of states measurements in disordered systems

A statistical method for measuring the modal density of elastic waves through direct mode counting in strongly scattering disordered systems is presented. To illustrate this approach, the results of ultrasonic experiments in a highly porous sintered glass bead network are reported. This method is shown to yield a reliable and robust measurement of the density of states, enabling mode-counting techniques to be applied to increasingly complex systems, where modal overlap and sensitivity to experimental conditions have previously hampered definitive results.

Diagnostic performance of the (1-->3)-beta-D-glucan assay for invasive fungal disease

BACKGROUND

Diagnosis of invasive fungal disease (IFD) is challenging, and it remains a significant cause of morbidity and mortality in immunocompromised patients. The (1-->3)-beta-D-glucan (BG) assay may be a useful adjunct, but its diagnostic performance is not well characterized.

METHODS

We retrospectively assessed the diagnostic indices of the BG assay in patients at risk of IFD who had a compatible clinical syndrome for the diagnosis of IFD a week after initial BG testing and at the end of the hospitalization associated with the first BG value. Patients with IFD were classified according to current European Organization for Research and Treatment of Cancer-Mycoses Study Group criteria, independent of BG results.

RESULTS

A total of 1308 BG assays were performed for 871 patients. One hundred twelve proven or probable IFD cases were diagnosed within 1 week after initial testing, and 116 cases were diagnosed by the end of hospitalization. Sensitivity of an initial BG level 80 pg/mL for IFD at 1 week was 0.64 (95% confidence interval [CI], 0.55-0.73), specificity was 0.84 (95% CI, 0.81-0.86), the positive likelihood ratio was 3.93 (95% CI, 2.94-5.26), and the negative likelihood ratio was 0.43 (95% CI, 0.31-0.59). Albumin, intravenous immunoglobulin, and hemodialysis were associated with elevated BG levels in patients without IFD (odds ratio, 4.78; 95% CI, 2.59-8.80). After excluding patients with these factors, specificity and the positive likelihood ratio of an initial BG level 80 pg/mL increased slightly. Empirical systemic antifungal treatment did not reduce overall BG sensitivity. Sensitivity was slightly lower among patients with hematologic malignancy or stem cell transplantation. Consideration of BG results would have increased the diagnostic certainty to probable in 54% of possible IFD cases.

CONCLUSIONS

BG level appears to be a fair diagnostic adjunct for IFD in patients with appropriate pretest probability and a suggestive clinical syndrome, especially when checked serially in patients not receiving factors associated with an elevated BG level in the absence of IFD.

Observation of multifractality in Anderson localization of ultrasound

We report the experimental observation of strong multifractality in wave functions below the Anderson localization transition in open three-dimensional elastic networks. Our results confirm the recently predicted symmetry of the multifractal exponents. We have discovered that the result of multifractal analysis of real data depends on the excitation scheme used in the experiment.

Plasma vitamin B(6) and risk of myocardial infarction in women

BACKGROUND

We prospectively evaluated the relationships between fasting plasma levels of vitamin B(6), as pyridoxal phosphate, and subsequent myocardial infarction risk in women.

METHODS AND RESULTS

Among 32 826 women who provided blood samples between 1989 and 1990 (27% of the original 1976 cohort), 239 were diagnosed with incident myocardial infarction (fatal and nonfatal) after blood collection but before July 1998. Of these women, 144 had provided a sample after fasting >10 hours. Cases were matched 1:2 by age, cigarette smoking status, and month of and fasting status at the time of blood collection with controls from the same cohort. Conditional logistic regression was used to adjust for potential confounders, including traditional coronary risk factors, anthropometric factors, dietary intake, and selected biomarkers. Median age at blood collection was 63 years. Plasma levels of pyridoxal phosphate were inversely associated with risk of myocardial infarction; the multivariable-adjusted rate ratio for the highest compared with the lowest quartiles (>70 versus <27.9 pmol/mL) was 0.22 (95% confidence interval, 0.09 to 0.55; P for trend=0.05). The association varied by age: among women who were <60 years of age at blood sampling, the rate ratio comparing the highest and lowest quartiles was 0.05 (95% confidence interval, 0.004 to 0.61), whereas among older women, the corresponding rate ratio was 0.36 (95% confidence interval, 0.13 to 1.02).

CONCLUSIONS

Fasting plasma concentration of pyridoxal phosphate was inversely associated with myocardial infarction risk, an effect that was in part independent of dietary B(6) intake. In addition to dietary vitamin B(6) intake, there are other determinants of plasma vitamin B(6) status, and these factors warrant further research.

Transmission of ultrasound through a single layer of bubbles

We investigate, both experimentally and theoretically, the effect of coupling between resonant scatterers on the transmission coefficient of a model system of isotropic scatterers. The model system consists of a monodisperse layer of bubbles, which exhibit a strong monopole scattering resonance at low ultrasonic frequencies. The layer was a true 2D structure obtained by injecting very monodisperse bubbles (with radius a approximately 100 microm) into a yield-stress polymer gel. Even for a layer with a low concentration of bubbles (areal fraction, n pi a(2), of 10-20%, where n is the number of bubbles per unit area), the ultrasonic transmission was found to be significantly reduced by the presence of bubbles (-20 to -50 dB) and showed a sharp minimum at a particular frequency. Interestingly, this frequency did not correspond to the resonance frequency of the individual, isolated bubbles, but depended markedly on the concentration. This frequency shift is an indication of strong coupling between the bubbles. We propose a simple model, based on a self-consistent relation, which takes into account the coupling between the bubbles and gives good agreement with the measured transmission coefficient.

Experimental and theoretical evidence for subwavelength imaging in phononic crystals

We show experimentally and theoretically that super resolution can be achieved while imaging with a flat lens consisting of a phononic crystal exhibiting negative refraction. This phenomenon is related to the coupling between the incident evanescent waves and a bound slab mode of the phononic crystal lens, leading to amplification of evanescent waves by the slab mode. Super resolution is only observed when the source is located very near to the lens, and is very sensitive to the location of the source parallel to the lens surface as well as to site disorder in the phononic crystal lattice.

Estimation of the disease-specific diagnostic marker distribution under verification bias

We consider the estimation of the parameters indexing a parametric model for the conditional distribution of a diagnostic marker given covariates and disease status. Such models are useful for the evaluation of whether and to what extent a marker's ability to accurately detect or discard disease depends on patient characteristics. A frequent problem that complicates the estimation of the model parameters is that estimation must be conducted from observational studies. Often, in such studies not all patients undergo the gold standard assessment of disease. Furthermore, the decision as to whether a patient undergoes verification is not controlled by study design. In such scenarios, maximum likelihood estimators based on subjects with observed disease status are generally biased. In this paper, we propose estimators for the model parameters that adjust for selection to verification that may depend on measured patient characteristics and additonally adjust for an assumed degree of residual association. Such estimators may be used as part of a sensitivity analysis for plausible degrees of residual association. We describe a doubly robust estimator that has the attractive feature of being consistent if either a model for the probability of selection to verification or a model for the probability of disease among the verified subjects (but not necessarily both) is correct.