Advanced Imaging and Receipt of Guideline Concordant Care in Women with Early Stage Breast Cancer.
Elizabeth Trice LoggersDiana S M BuistLaura S GoldSteven ZeliadtRachel Hunter MerrillRuth EtzioniScott D RamseySean D SullivanLarry KesslerPublished in: International journal of breast cancer (2016)
Objective. It is unknown whether advanced imaging (AI) is associated with higher quality breast cancer (BC) care. Materials and Methods. Claims and Surveillance Epidemiology and End Results data were linked for women diagnosed with incident stage I-III BC between 2002 and 2008 in western Washington State. We examined receipt of preoperative breast magnetic resonance imaging (MRI) or AI (defined as computed tomography [CT]/positron emission tomography [PET]/PET/CT) versus mammogram and/or ultrasound (M-US) alone and receipt of guideline concordant care (GCC) using multivariable logistic regression. Results. Of 5247 women, 67% received M-US, 23% MRI, 8% CT, and 3% PET/PET-CT. In 2002, 5% received MRI and 5% AI compared to 45% and 12%, respectively, in 2008. 79% received GCC, but GCC declined over time and was associated with younger age, urban residence, less comorbidity, shorter time from diagnosis to surgery, and earlier year of diagnosis. Breast MRI was associated with GCC for lumpectomy plus radiation therapy (RT) (OR 1.55, 95% CI 1.08-2.26, and p = 0.02) and AI was associated with GCC for adjuvant chemotherapy for estrogen-receptor positive (ER+) BC (OR 1.74, 95% CI 1.17-2.59, and p = 0.01). Conclusion. GCC was associated with prior receipt of breast MRI and AI for lumpectomy plus RT and adjuvant chemotherapy for ER+ BC, respectively.
Keyphrases
- positron emission tomography
- computed tomography
- contrast enhanced
- pet ct
- magnetic resonance imaging
- estrogen receptor
- artificial intelligence
- healthcare
- diffusion weighted imaging
- dual energy
- quality improvement
- image quality
- early stage
- radiation therapy
- magnetic resonance
- palliative care
- pet imaging
- high resolution
- minimally invasive
- polycystic ovary syndrome
- big data
- machine learning
- type diabetes
- patients undergoing
- deep learning
- pain management
- risk factors
- breast cancer cells
- south africa
- percutaneous coronary intervention
- pregnant women
- metabolic syndrome
- cardiovascular disease
- cervical cancer screening
- fluorescence imaging
- locally advanced
- rectal cancer
- coronary artery bypass
- atrial fibrillation