scholarly journals Geographic Disparities of Alzheimer’s Disease Mortality in Females With Breast Cancer

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 60-60
Author(s):  
Igor Akushevich ◽  
Arseniy Yashkin ◽  
Julia Kravchenko
Keyword(s):  
Breast Cancer ◽  
Death Certificate ◽  
East Coast ◽  
Mortality Rates ◽  
Administrative Claims ◽  
Breast Cancer Patients ◽  
Geographic Disparities ◽  
Socioeconomic Characteristics ◽  
Medicare Data ◽  
Disease Mortality

Abstract Our estimates showed significant gaps in mortality rates between the West and East parts of the U.S. when these rates are based on death certificate data. These geographic disparities were persistent over time and could not be fully explained by differences in demographic and socioeconomic characteristics, comorbidities, and/or differences in AD coding between these regions. However, incidence and incidence-based mortality rates based on Medicare data do not reproduce these geographic disparities. Death certificate-based patterns hold for the subset of the population with breast cancer, e.g., for subpopulation for which breast cancer was listed as a secondary cause of death. Therefore, SEER-Medicare data, which contains both death-certificate records and Medicare administrative claims for the same individuals can be used to resolve this inconsistency in findings. Analysis of breast cancer patients from two SEER registries in NJ and WA states in SEER-Medicare data (2000-2013) showed that the fraction of deceased individuals with an underlying cause AD among those who had a Medicare diagnosis of AD is 2.5-3.5 times (depending on the Medicare ascertainment algorithm) higher in WA comparing to NJ (p<0.0001). The odds ratio of not-having AD as an underlying cause is 1.3 for WA vs. NJ and increases with age, for non-white races, and unmarried individuals. Our findings do not support the hypothesis of higher rates of AD in WA state but show that AD is likely underrepresented in death certificate in NJ and possibly other East coast states.

Fertility preservation in young breast cancer patients: A population-based study.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 90-90
Author(s):  
Diana Nguyen ◽  
Ghader Jamjoum ◽  
Ari N. Meguerditchian
Keyword(s):  
Breast Cancer ◽  
Fertility Preservation ◽  
Service Use ◽  
Estrogen Therapy ◽  
Population Based ◽  
Administrative Claims ◽  
Breast Cancer Patients ◽  
Population Based Study ◽  
Young Breast Cancer ◽  
Universal Health

90 Background: Treatment-related infertility is an important cause of distress in young women with breast cancer (YWBC) that is preventable by fertility preservation (FP) prior to initiating therapy. This study assesses FP service use by YWBC in Quebec (Canada). Methods: Administrative claims for women ≤ 40 diagnosed between 01-04-2012 and 31-03-2018 were identified using Quebec’s universal health services database (RAMQ). Access to and use of FP services were ascertained by identifying claims for a visit with an obstetrician/gynecologist (OB/GYN) ≤ 90 days of diagnosis, followed by claims for ovarian stimulation, ovule harvesting or artificial insemination. Patient, disease and treatment-related predictors were estimated using logistic regression. Results: 1 616 YWBC were treated. Mean age was 36 (SD 4.1), 72.1% had a CCI = 0, 84.5% were urban residents, and 72.2% experienced some form of socioeconomical disadvantages. Stage distribution was: 0.93%, 68.8, and 30.3% for stages 0, 1-2, and 3 respectively. 53.0% had a mastectomy, 40.8% received chemotherapy (CT), 70.7% received radiotherapy, 20.9% initiated anti-estrogen therapy. 387 YWBC consulted an OB/GYN within 90 days of diagnosis and 155 subsequently received FP services. Predictors associated with FP use included: decreased age (OR= 0.82, 95CI = 0.79-0.86), type of surgery (OR = 0.46, CI = 0.22-0.97), social isolation (OR =1.39, 95CI = 0.99-1.96) and receipt of chemotherapy (OR = 1.74, 95CI = 1.10-2.76). Conclusions: Only 23.9% of eligible YWBC in Quebec accessed FP specialists. Of these, 40.1% chose to move forward with FP. These findings raise important questions on how to optimize access to FP expertise. [Table: see text]

Costs of administration of intravenous (IV) therapies in early versus late stage breast cancer in a US population

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 6588-6588
Author(s):  
G. B. Kruse ◽  
M. M. Amonkar ◽  
D. Skonieczny ◽  
G. L. Smith
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Late Stage ◽  
Early Stage ◽  
Administrative Claims ◽  
Cancer Drugs ◽  
Breast Cancer Patients ◽  
Related Services ◽  
Specialized Equipment ◽  
Cost Components

6588 Background: There are significant costs associated with IV administration of cancer drugs ranging from adverse events associated with the administration to the need for specialized equipment, supplies and personnel time. This study utilized a novel provider-payer contract database to compare the cost components of providing IV therapy to women with early and late stage breast cancer. Methods: Women diagnosed with breast cancer (ICD-9 code 174) between 01/01/2003 and 05/31/2006 and receiving IV monotherapy were identified from an administrative claims database of >60 multi-specialty medical practices/clinics (additional ICD-9 codes 196–198 used to identify late stage breast cancer). Costs were estimated on a per IV administration visit basis using the allowable amount for a claim which closely represents the actual amount paid to providers. Published literature was used to categorize the various billable cost components. Results: 1,393 early and 828 late stage breast cancer patients receiving any of 11 IV breast cancer drugs were identified. The costs breakdown by category for all drugs and for the 2 most commonly used drugs, per IV administration visit, is presented in the table . Conclusions: Costs associated with administration of IV therapies and other visit-related services constituted more than 36% of total costs for early stage and 41% of total costs for late stage breast cancer patients. These costs represent a significant cost burden to payers. Maximization of valuable resources could be effected by increased use of effective oral therapies for treatment of breast cancer. [Table: see text] [Table: see text]

Machine learning to predict tamoxifen adherence among U.S. commercially insured breast cancer patients.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 276-276
Author(s):  
Tyler J. O'Neill ◽  
Vishakha Sharma ◽  
Athanasios Siadimas ◽  
Amir Babaeian ◽  
Gayathri Yerrapragada
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Logistic Regression ◽  
Predictive Value ◽  
Treatment Initiation ◽  
Predictive Accuracy ◽  
Metastatic Breast ◽  
Cost Of Care ◽  
Administrative Claims ◽  
Breast Cancer Patients

276 Background: Adherence to tamoxifen among women diagnosed with hormone receptor positive metastatic breast cancer (mBC) can improve survival and minimize recurrence. Screening for non-adherence at treatment initiation may support personalized care, improve health outcomes, and minimize cost of care. This study aimed to use real world data (RWD) and machine learning (ML) methods to classify tamoxifen non-adherence. Methods: A cohort of women diagnosed with incident mBC from 2012 to 2018 were identified from Truven MarketScan Commercial Claims and Encounters and Medicare supplemental administrative claims databases. Patients with < 80% proportion of days coverage (PDC) in the year following treatment initiation were classified non-adherent. Training and internal validation cohorts were randomly generated (4:1 ratio). Clinical procedures, comorbidity, treatment and healthcare encounter features in the year prior to treatment initiation were used to train logistic regression, boosted logistic regression, random forest, and feed forward neural network models and internally validated based on area under receiver operating characteristic (AUROC) curve. The most predictive ML approach was evaluated to assess feature importance. Results: A total of 3,022 patients were included with 39.9% classified as non-adherent. All ML models had moderate predictive accuracy. Logistic regression (AUROC 0.64) was easily interpreted with sensitivity 94% (95% confidence interval [CI]: 0.89, 0.92) and specificity 0.31 (95% CI: 0.29, 0.33). The model accurately classified adherence (negative predictive value 88.7%) but was non-discriminate for non-adherence (positive predictive value 47.7%). Variable importance identified top predictive factors, including patient features (≥55 years old) and pre-treatment procedures (lymphatic nuclear medicine, radiation oncology, arterial surgery). Conclusions: ML using baseline administrative data predicts tamoxifen adherence. Baseline claims may not be sufficient to predict treatment non-adherence. Further validation with enriched longitudinal data may improve model performance for incorporation of predictions into clinical decision support.

scholarly journals Personalized models of breast cancer desmoplasia reveal biomechanical determinants of drug penetration

2021 ◽  
Author(s):  
Giovanni S Offeddu ◽  
Kristina Haase ◽  
Zhengpeng Wan ◽  
Luca Possenti ◽  
Huu Tuan Nguyen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Vascular Dysfunction ◽  
Fluid Pressure ◽  
Drug Distribution ◽  
Drug Efficacy ◽  
Patient Specific ◽  
Breast Cancer Patients ◽  
Disease Mortality ◽  
Key Aspects

Breast cancer desmoplasia heterogeneity contributes to high disease mortality due to discrepancies in treatment efficacy between patients. Personalized in vitro breast cancer models can be used for high throughput testing and ranking of therapeutic strategies to normalize the aberrant microenvironment in a patient-specific manner. Here, tumoroids assembled from patient-derived cells cultured in microphysiological systems including perfusable microvasculature reproduce key aspects of stromal and vascular dysfunction. Increased hyaluronic acid and collagen deposition, loss of vascular glycocalyx and reduced perfusion, and elevated interstitial fluid pressure in the models result in impaired drug distribution to tumor cells. We demonstrate the application of these personalized models as tools to rank molecular therapies for the normalization of the tumoroid microenvironment and to discover new therapeutic targets such as IL8 and CD44, which may ultimately improve drug efficacy in breast cancer patients.

Improved outcomes among breast cancer patients with more frequent mammography screening.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19146-e19146
Author(s):  
Ying Liu ◽  
Aliza Gordon ◽  
Michael Eleff ◽  
John Barron ◽  
Winnie Chi
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Screening Mammography ◽  
Administrative Claims ◽  
Cancer Stage ◽  
Stage At Diagnosis ◽  
Breast Cancer Patients ◽  
Invasive Treatment ◽  
The Impact

e19146 Background: Guidelines for optimal frequency of screening mammography (annual, biennial, never/choice of patient) vary by professional society, due to mixed or insufficient evidence regarding its benefits and harms. Little evidence exists on the impact of screening frequency, rather than any screening, on health outcomes. In this study, we measured differences in cancer stage at diagnosis, treatment rendered, mortality, and cost of treatment for women with different numbers of screenings prior to breast cancer diagnosis. Methods: Utilizing administrative claims, we identified 25,492 women aged 44 or older with various numbers of mammographic screening ≥ 11 months apart during the four years prior to their incident breast cancer diagnosis from 2010 to 2018. Outcomes were assessed during the six months following diagnosis. Regression models were used to compare women with differing numbers of mammograms (0, 1, 2, 3, or 4/5), adjusting for demographic characteristics and baseline comorbidities. Results: More screenings were associated with less advanced cancer at diagnosis, higher rates in lumpectomy and radiation, lower rates in mastectomy and chemotherapy, lower costs and mortality within 6 months post diagnosis (Table). Results were similar in a subgroup with only women aged 44-49 at diagnosis (not shown). Conclusions: Increased frequency of screening mammography is associated with earlier breast cancer stage at diagnosis, less toxic and invasive treatment, lower mortality, and lower cost, including for women under age 50. [Table: see text]

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