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437 Background: Optimizing post-operative clinical management for early-stage (I/II) colorectal cancer (CRC) patients (pts) is a significant unmet medical need. We hypothesized that a molecular prognostic test using primary CRC tissue would better predict the chances of tumor R within 36 months (mo) than current NCCN Clinical Practice Guidelines (NCCN). Methods: Pts had tumor R by 36 mo (n=46) or confirmed non-recurrence (NR) for ≥36 mo (n=69) after surgery; none had received neoadjuvant or adjuvant therapy. Archival formalin-fixed paraffin-embedded primary adenocarcinoma tissues (median storage 7 years; range 4-15) obtained at initial surgical resection with curative intent were retrieved for 86 stage I/II (pT1-4 pN0 M0) colon cancer and 29 stage I (pT1-2, pN0 M0) rectal cancer pts from 2 US and 2 European sites that were different from those previously used to generate the molecular test. Tumor gene expression was assessed by qRT-PCR with custom 384- well TaqMan Low Density Arrays (Applied Biosystems) using RNA that had satisfied a set of rigorous quality control parameters. Results: For stages I/II CRC (n=115), the dichotomous rule correctly classified 32/46 R and 38/69 NR pts: sensitivity (S) 0.70, specificity (SP) 0.55. High-risk pts had a significantly higher probability of R by 36 mo than low-risk pts: PPV 0.51, NPV 0.73; hazard ratio (HR) 2.06 (95% CI: 1.10 to 3.86; p=0.020). NCCN (V.1.2011) was not able to differentiate 36-mo R vs NR in this population: S 0.72, SP 0.42, PPV 0.45, NPV 0.69; HR 1.38 (95% CI: 0.73 to 2.63; p=0.315). The SP of the molecular test was significantly greater than that for NCCN (p=0.05). For stage I pts (n=29; 13R, 16NR), the prognostic accuracy of the test (0.79; 23/29) surpassed that for NCCN (0.55; 16/29). Conclusions: External validation of a 5-gene prognostic rule confirmed its ability to differentiate early stage CRC pts at high risk vs low risk for R within 36 mo after surgery better than current NCCN Guidelines, especially for stage I. The improved specificity and high sensitivity of the molecular test confirm its potential utility for optimizing post-op clinical management of early stage CRC. [Table: see text]

Numerical laboratory data at admission have been proposed for enhancement of inpatient predictive modeling from administrative claims. In this study, predictive models for inpatient/30-day postdischarge mortality and for risk-adjusted prolonged length of stay, as a surrogate for severe inpatient complications of care, were designed with administrative data only and with administrative data plus numerical laboratory variables. A comparison of resulting inpatient models for acute myocardial infarction, congestive heart failure, coronary artery bypass grafting, and percutaneous cardiac interventions demonstrated improved discrimination and calibration with administrative data plus laboratory values compared to administrative data only for both mortality and prolonged length of stay. Improved goodness of fit was most apparent in acute myocardial infarction and percutaneous cardiac intervention. The emergence of electronic medical records should make the addition of laboratory variables to administrative data an efficient and practical method to clinically enhance predictive modeling of inpatient outcomes of care.

Predictive modeling for postdischarge outcomes of inpatient care has been suboptimal. This study evaluated whether admission numerical laboratory data added to administrative models from New York and Minnesota hospitals would enhance the prediction accuracy for 90-day postdischarge deaths without readmission (PD-90) and 90-day readmissions (RA-90) following inpatient care for cardiac patients. Risk-adjustment models for the prediction of PD-90 and RA-90 were designed for acute myocardial infarction, percutaneous cardiac intervention, coronary artery bypass grafting, and congestive heart failure. Models were derived from hospital claims data and were then enhanced with admission laboratory predictive results. Case-level discrimination, goodness of fit, and calibration were used to compare administrative models (ADM) and laboratory predictive models (LAB). LAB models for the prediction of PD-90 were modestly enhanced over ADM, but negligible benefit was seen for RA-90. A consistent predictor of PD-90 and RA-90 was prolonged length of stay outliers from the index hospitalization.

ObjectiveAssess algorithms for linking patients across de‐identified databases without compromising confidentiality.Data Sources/Study SettingHospital discharges from 11 Mayo Clinic hospitals during January 2008–September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data).Study DesignCross‐sectional assessment of sensitivity and positive predictive value (PPV) for four linking algorithms tested by identifying readmissions and posthospital mortality on the assessment data with application to statewide data.Data Collection/Extraction MethodsDe‐identified claims included patient gender, birthdate, and zip code. Assessment records were matched with institutional sources containing unique identifiers and the last four digits of Social Security number (SSNL4).Principal FindingsGender, birthdate, and five‐digit zip code identified readmissions with a sensitivity of 98.0 percent and a PPV of 97.7 percent and identified postdischarge mortality with 84.4 percent sensitivity and 98.9 percent PPV. Inclusion of SSNL4 produced nearly perfect identification of readmissions and deaths. When applied statewide, regions bordering states with unavailable hospital discharge data had lower rates.ConclusionAddition of SSNL4 to administrative data, accompanied by appropriate data use and data release policies, can enable trusted repositories to link data with nearly perfect accuracy without compromising patient confidentiality. States maintaining centralized de‐identified databases should add SSNL4 to data specifications.

Background— Revascularization strategies often hinge on the presence and degree of left anterior descending coronary artery (LAD) stenosis. A decision for bypass surgery is often based on the durability of surgical LAD revascularization compared with percutaneous approaches. By decreasing restenosis, drug-eluting stents may have reduced the “reintervention gap” between surgery and percutaneous intervention, making the percutaneous route preferable. Methods and Results— Of the 1101 patients in the SIRIUS trial, 459 with an LAD stenosis were randomized to percutaneous intervention with either sirolimus-eluting or bare-metal stents. Baseline demographic, clinical, and angiographic data were obtained. Patients had 1-year clinical and 8-month angiographic follow-up. Baseline characteristics were similar in both groups. The majority of lesions were tubular type B lesions (69.7%) with a mean diameter of 2.73 mm and a mean length of 14.0 mm. The binary in-stent restenosis rate was 2% for the sirolimus stent group and 41.6% for the bare-metal arm (relative risk, 0.05; 95% CI, 0.02 to 0.1; P <0.001). One-year major adverse events (defined as cardiac death, Q-wave and non–Q-wave myocardial infarction, or target vessel revascularization) was decreased 59% in the sirolimus-stent group (9.8% versus 24.9%; relative risk, 0.39; 95% CI, 0.26 to 0.61; P <0.001). Subgroup analysis of 135 patients with proximal LAD lesions showed similar benefits. In-stent restenosis was 0 in the proximal LAD sirolimus-eluting group (n=67), compared with 38% in the bare-metal arm (n=68), and major adverse events demonstrated a similar trend, with a 50% decrease compared with control patients (10.4% versus 20.6%, P =NS). Conclusions— Sirolimus-eluting stents significantly decrease revascularization rates in LAD lesions. At 1 year, sirolimus-eluting stent revascularization rates are comparable to historic single vessel bypass surgery revascularization rates.