Association of genetic polymorphisms with local steroid metabolism in human benign breasts.

PURPOSE: Although alterations of concentrations in circulating steroids have been linked to single nucleotide polymorphisms (SNPs) of steroidogenic enzymes, we hypothesized that SNPs of such enzymes located within the breast affect local steroid concentrations more than products of such SNPs absorbed from the circulation. METHODS: Steroids (estradiol, estrone, testosterone, androstenedione, DHEA, DHEA sulfate, progesterone) in nipple aspirate fluid (NAF) were purified by HPLC and they along with serum steroids were quantified by immunoassays. Polymorphisms of the transporter SLCO2B1 and enzymes HSD3B1, CYP19A1, HSD17B12, AKR1C3, CYP1B1, and SRD5A1 were measured in white blood cell DNA. RESULTS: Steroid concentrations in NAF of subjects with homozygous minor genotypes differed from those with heterozygotes, i.e., SLCO2B1 (rs2851069) decreased DHEAS (p = 0.04), HSD17B12 (rs11555762) increased estradiol (p < 0.004), and CYP1B1 (rs1056836) decreased estradiol (p = 0.017) and increased progesterone (p = 0.05). Also, in serum, CYP19A1 (rs10046 and rs700518) both decreased testosterone (p = 0.02) and SRD5A1 increased androstenedione (p = 0.006). Steroids in subjects with major homozygotes did not differ from those with heterozygotes indicating recessive characteristics. CONCLUSIONS: In the breast, SNPs were associated with decreased uptake of DHEAS (SLCO2B1), increased estradiol concentrations through increased oxidoreductase activity (HSD17B12), or decreased estradiol concentrations by presumed formation of 4-hydroxyestradiol (CYP1B1). CYP19A1 was associated with decreased testosterone concentrations in serum but had no significant effect on estrogen or androgen concentrations within the breast. The hormone differences observed in NAF were not usually evident in serum, indicating the importance of assessing the effect of these SNPs within the breast.

Risk of discharge to postacute care: a patient-centered outcome for the american college of surgeons national surgical quality improvement program surgical risk calculator.

IMPORTANCE: Individualized risk prediction tools have an important role as decision aids for use by patients and surgeons before surgery. Patient-centered outcomes should be incorporated into such tools to widen their appeal and improve their usability. OBJECTIVE: To develop a patient-centered outcome for the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator, a web-based, individualized risk prediction tool. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study using data from the ACS NSQIP, a national clinical data registry. A total of 973 211 patients from July 2010 to June 2012, encompassing 392 hospitals, were used in this analysis. MAIN OUTCOMES AND MEASURES: Risk of discharge to a postacute care setting. RESULTS: The overall rate of discharge to postacute care was 8.8%. Significant predictors of discharge to postacute care included being 85 years or older (odds ratio [OR] = 9.17; 95% CI, 8.84-9.50), the presence of septic shock (OR = 2.43; 95% CI, 2.20-2.69) or ventilator dependence (OR = 2.81; 95% CI, 2.56-3.09) preoperatively, American Society of Anesthesiologists class of 4 or 5 (OR = 3.59; 95% CI, 3.46-3.71), and totally dependent functional status (OR = 2.27; 95% CI, 2.11-2.44). The final model predicted risk of discharge to postacute care with excellent accuracy (C statistic = 0.924) and calibration (Brier score = 0.05). CONCLUSIONS AND RELEVANCE: Individualized risk of discharge to postacute care can be predicted with excellent accuracy. This outcome will be incorporated into the ACS NSQIP Surgical Risk Calculator.

Effect of postoperative complications on adjuvant chemotherapy use for stage III colon cancer.

OBJECTIVE: The National Quality Forum has endorsed a quality metric concerning the use of adjuvant chemotherapy administration in stage III colon cancer, yet a substantial treatment gap exists. Our objective was to evaluate the association of postoperative complications on the use of adjuvant therapy after colectomy for cancer. PATIENTS AND METHODS: Data from the American College of Surgeons National Surgical Quality Improvement Program and National Cancer Data Base were linked to augment cancer registry information with robust clinical data on comorbidities and postoperative complications (2006-2008). The association of complications on adjuvant chemotherapy use was assessed using hierarchical multivariable regression models. RESULTS: From 126 hospitals, 2368 patients underwent resection for stage III colon adenocarcinoma. Overall utilization of adjuvant chemotherapy was 63.2% (1497/2368). Of the 871 patients who did not receive chemotherapy, 652 met National Quality Forum exclusion criteria: death, severe comorbidity, refusal of care, advanced age (≥80 years), or prior malignancy. Of the remaining 219 patients, 19.1% (42/219) had 1 or more serious postoperative complications (eg, pneumonia, pulmonary failure). After accounting for the aforementioned potential explanations, the utilization rate was 87.2% (1497/1716). The strongest predictors of adjuvant chemotherapy omission were prolonged postoperative ventilation, renal failure, reintubation, and pneumonia (all Ps < 0.05). Superficial surgical site infection did not decrease adjuvant therapy receipt but delayed the time to its use by 3-fold. Serious complications increased time to chemotherapy by 65%. Abscess/anastomotic leak increased time to adjuvant chemotherapy by more than 5-fold. CONCLUSIONS: Serious postoperative complications explained nearly 20% of the adjuvant chemotherapy treatment gap for patients with stage III colon cancer. The use of clinical data remains important when judging provider performance.

Hormonal determinants of nipple aspirate fluid yield among breast cancer cases and screening controls.

BACKGROUND: Nipple aspiration fluid (NAF) use as a biosample is limited by the variable yield across studies. We investigated the endocrine determinants of yield in an ongoing breast cancer case-control study. METHODS: One-hundred and eighteen women yielding ≥2 µL NAF and 120 non-yielders were included; serum hormones were measured; differences in median hormones were assessed using the Wilcoxon rank-sum test. ORs and 95% confidence intervals (95% CI) for yielder status relative to hormone levels were estimated using logistic regression, adjusting for parity and lactation, and, in premenopausal women, menstrual cycle phase (MCP). RESULTS: Prolactin concentrations were higher in yielders than non-yielders (premenopausal: 7.6 and 2.5 ng/mL, P < 0.01; postmenopausal 5.3 and 2.2 ng/mL; P < 0.01). Among premenopausal-yielders, estradiol was lower (64.3 vs. 90.5 pg/mL, MCP-adjusted P = 0.02). In separate menopausal status and parity-adjusted models, significant case-control differences persisted in prolactin: case OR 1.93 (95% CI, 1.35-2.77), control OR 1.64 (95% CI, 1.17-2.29). Premenopausal control yielders had higher progesterone (OR, 1.70; 95% CI, 1.18-2.46) and sex-hormone binding-globulin (OR, 2.09; 95% CI, 1.08-4.05) than non-yielders. Among parous women, further adjustment for lactation suggested a stronger positive association of serum prolactin with yield in cases than controls. CONCLUSION: NAF-yielders show higher prolactin than non-yielders, regardless of menopause and parity; implications of this and other endocrine differences on NAF biomarkers of breast cancer risk deserve further study. IMPACT: NAF yield is associated with a distinct endocrine environment that must be considered in studies of NAF-based breast cancer risk markers.

Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons.

BACKGROUND: Accurately estimating surgical risks is critical for shared decision making and informed consent. The Centers for Medicare and Medicaid Services may soon put forth a measure requiring surgeons to provide patients with patient-specific, empirically derived estimates of postoperative complications. Our objectives were to develop a universal surgical risk estimation tool, to compare performance of the universal vs previous procedure-specific surgical risk calculators, and to allow surgeons to empirically adjust the estimates of risk. STUDY DESIGN: Using standardized clinical data from 393 ACS NSQIP hospitals, a web-based tool was developed to allow surgeons to easily enter 21 preoperative factors (demographics, comorbidities, procedure). Regression models were developed to predict 8 outcomes based on the preoperative risk factors. The universal model was compared with procedure-specific models. To incorporate surgeon input, a subjective surgeon adjustment score, allowing risk estimates to vary within the estimate's confidence interval, was introduced and tested with 80 surgeons using 10 case scenarios. RESULTS: Based on 1,414,006 patients encompassing 1,557 unique CPT codes, a universal surgical risk calculator model was developed that had excellent performance for mortality (c-statistic = 0.944; Brier score = 0.011 [where scores approaching 0 are better]), morbidity (c-statistic = 0.816, Brier score = 0.069), and 6 additional complications (c-statistics > 0.8). Predictions were similarly robust for the universal calculator vs procedure-specific calculators (eg, colorectal). Surgeons demonstrated considerable agreement on the case scenario scoring (80% to 100% agreement), suggesting reliable score assignment between surgeons. CONCLUSIONS: The ACS NSQIP surgical risk calculator is a decision-support tool based on reliable multi-institutional clinical data, which can be used to estimate the risks of most operations. The ACS NSQIP surgical risk calculator will allow clinicians and patients to make decisions using empirically derived, patient-specific postoperative risks.

Effect of including cancer-specific variables on models examining short-term outcomes.

BACKGROUND: The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) generally has not collected cancer-specific variables. Because increasing numbers of studies are using ACS NSQIP data to study cancer surgery, the objectives of the current study were 1) to examine differences between existing ACS NSQIP variables and cancer registry variables, and 2) to determine whether the addition of cancer-specific variables improves modeling of short-term outcomes. METHODS: Data from patients in the ACS NSQIP and National Cancer Data Base (NCDB) who underwent colorectal resection for cancer were linked (2006-2008). By using regression methods, the relative importance of cancer staging and neoadjuvant therapy variables were assessed along with their effects on morbidity, serious morbidity, and mortality. RESULTS: From 146 hospitals, 11,405 patients were identified who underwent surgery for colorectal cancer (colon, 85%; rectum, 15%). The NCDB metastatic cancer variable and the ACS NSQIP disseminated cancer variables agreed marginally (Cohen kappa coefficient, 0.454). For mortality, only the ACS NSQIP disseminated cancer variable and the NCDB stage IV variable were identified as important predictors; whereas the variables stage I through III, tumor (T)-classification, and lymph node (N)-classification were not selected. Cancer stage variables were inconsistently important for serious morbidity (stage IV, T-classification), superficial surgical site infection (N-classification), venous thromboembolism (metastatic cancer), and pneumonia (T-classification). With respect to neoadjuvant therapy, ACS NSQIP and NCDB variables agreed moderately (kappa, 0.570) and predicted superficial surgical site infection, serious morbidity, and organ space surgical site infection. The model fit was similar regardless of the inclusion of stage and neoadjuvant therapy variables. CONCLUSIONS: Although advanced disease stage and neoadjuvant therapy variables were predictors of short-term outcomes, their inclusion did not improve the models.

Development of an online morbidity, mortality, and near-miss reporting system to identify patterns of adverse events in surgical patients.

OBJECTIVES: To design a Web-based system to track adverse and near-miss events, to establish an automated method to identify patterns of events, and to assess the adverse event reporting behavior of physicians. DESIGN: A Web-based system was designed to collect physician-reported adverse events including weekly Morbidity and Mortality (M&M) entries and anonymous adverse/near-miss events. An automated system was set up to help identify event patterns. Adverse event frequency was compared with hospital databases to assess reporting completeness. SETTING: A metropolitan tertiary care center. MAIN OUTCOME MEASURES: Identification of adverse event patterns and completeness of reporting. RESULTS: From September 2005 to August 2007, 15,524 surgical patients were reported including 957 (6.2%) adverse events and 34 (0.2%) anonymous reports. The automated pattern recognition system helped identify 4 event patterns from M&M reports and 3 patterns from anonymous/near-miss reporting. After multidisciplinary meetings and expert reviews, the patterns were addressed with educational initiatives, correction of systems issues, and/or intensive quality monitoring. Only 25% of complications and 42% of inpatient deaths were reported. A total of 75.2% of adverse events resulting in permanent disability or death were attributed to the nature of the disease. Interventions to improve reporting were largely unsuccessful. CONCLUSIONS: We have developed a user-friendly Web-based system to track complications and identify patterns of adverse events. Underreporting of adverse events and attributing the complication to the nature of the disease represent a problem in reporting culture among surgeons at our institution. Similar systems should be used by surgery departments, particularly those affiliated with teaching hospitals, to identify quality improvement opportunities.