Trajectories of Pain After Cardiac Surgery: Implications for Measurement, Reporting, and Individualized Treatment.

BACKGROUND: Postoperative pain after cardiac surgery is a significant problem, but studies often report pain value as an average of the study cohort, obscuring clinically meaningful differences in pain trajectories. We sought to characterize heterogeneity in postoperative pain experiences. METHODS: We enrolled patients undergoing a cardiac surgery at a tertiary care center between January 2019 and February 2020. Participants received an electronically-delivered questionnaire every 3 days for 30 days to assess incision site pain level. We evaluated the variability in pain trajectories over 30 days by the cohort-level mean with confidence band and latent classes identified by group-based trajectory model. Group-based trajectory model estimated the probability of belonging to a specific trajectory of pain. RESULTS: Of 92 patients enrolled, 75 provided ≥3 questionnaire responses. The cohort-level mean showed a gradual and consistent decline in the mean pain level, but the confidence bands covered most of the pain score range. The individual-level trajectories varied substantially across patients. Group-based trajectory model identified 4 pain trajectories: persistently low (n=9, 12%), moderate declining (initially mid-level, followed by decline; n=26, 35%), high declining (initially high-level, followed by decline; n=33, 44%), and persistently high pain (n=7, 9%). Persistently high pain and high declining groups did not seem to be clearly distinguishable until approximately postoperative day 10. Patients in persistently low pain trajectory class had a numerically lower median age than the other 3 classes and were below the lower confidence band of the cohort-level approach. Patients in the persistently high pain trajectory class had a longer median length of hospital stay than the other 3 classes and were often higher than the upper confidence band of the cohort-level approach. CONCLUSIONS: We identified 4 trajectories of postoperative pain that were not evident from a cohort-level mean, which has been a common way of reporting pain level. This study provides key information about the patient experience and indicates the need to understand variation among sites and surgeons and to investigate determinants of different experience and interventions to mitigate persistently high pain.

Relationship of surgeon experience and outcomes of surgery for degenerative mitral valve disease.

OBJECTIVE: To assess the impact of surgeon experience on the outcomes of degenerative mitral valve disease. METHODS: We reviewed all patients who had surgery for degenerative mitral valve disease between 2011 and 2016. Experienced surgeon was defined as performing ≥ 25 mitral valve operations/year. Patient characteristics and outcomes were compared. Competing risk analysis was performed to identify factors associated with mitral regurgitation (MR) recurrence. Survival analysis for mortality was done using Kaplan Meier curve and Cox proportional hazard method. RESULTS: There were 575 patients treated by 9 surgeons for severe MR caused by degenerative mitral valve disease between 2011 and 2016. Three experienced surgeons performed 77.2% of the operations. Patients treated by less experienced surgeons had worse comorbidity profile and were more likely to have an urgent or emergent operation (p = .001). Experienced surgeons were more likely to attempt repair (p = .024), to succeed in repair (94.7% vs. 87%; p = .001), had shorter cross-clamp times (p = .001), and achieved higher repair rate (81.3% vs. 69.7%; p = .005). Experienced surgeons were more likely to use neochordae (p = .001) and less likely to use chordae transfer (p = .001). Surgeon experience was not associated with recurrence of moderate or higher degree of MR after repair but was an independent risk factor for mortality (HR = 2.64; p = .002). CONCLUSIONS: Techniques of degenerative mitral valve surgery differ with surgeon experience, with higher rates of repair and better outcomes associated with more experienced surgeons.

Center-level CABG and valve operative outcomes and volume-outcome relationships in New York State.

BACKGROUND: We analyzed center-level outcome correlations between valve surgery and coronary artery bypass graft (CABG) in New York (NY) State and how volume-outcome effect differ between case types. METHODS: We used the 2014-2016 NY cardiac surgery outcomes report. Center-level observed to-expected (observed-to-expected ratio [O/E]) ratio for operative mortality provided risk-adjusted operative outcomes for isolated CABG and valve operations. Correlation coefficient characterized the concordance in center-level outcomes in CABG and valve. Discordant outcomes were defined as having O/E ratio greater than 2 in one operation type with O/E ratio ≤1 in another. Linearized slope of volume-outcome effect in case types offered insights into centers with discordant performances between procedures. RESULTS: Among 37 NY centers, annual center volumes were 220 ± 120 cases for CABG and 190 ± 178 cases for valve operations. Modest center-level correlation between CABG and valve O/E ratio was shown (R2 = 0.31). Two centers had discordant performance between valve and CABG (O/E ≤ 1 for CABG while O/E > 2 for valve procedures). No centers had CABG O/E ratio greater than 2 while valve O/E ratio ≤1. Linearized slope describing volume-outcome effects showed stronger effect in valve operations compared to CABG: O/E ratio declined 0.1 units per 100 CABG volume increase, while O/E ratio declined 0.33 units per 100 valve volume increase. CONCLUSION: In NY hospitals, favorable valve outcomes may indicate good CABG outcomes but good CABG outcomes may not ensure valve outcomes. Outcome variation in valve operation could be related to stronger volume-outcome effect in valve operations relative to CABG. Valve operations may benefit from regionalization.

Association Between Clinical Value and Financial Cost of Cancer Treatments: A Cross-Sectional Analysis.

BACKGROUND: The cost of cancer treatment has increased significantly in recent decades, but it is unclear whether these costs have been associated with commensurate improvement in clinical value. This study aimed to assess the association between the cost of cancer treatment and 4 of the 5 NCCN Evidence Blocks (EB) measures of clinical value: efficacy of regimen/agent, safety of regimen/agent, quality of evidence, and consistency of evidence. METHODS: This is a cross-sectional, observational study. We obtained NCCN EB ratings for all recommended, first-line, and/or maintenance treatments for the 30 most prevalent cancers in the United States and calculated direct pharmacologic treatment costs (drug acquisition, administration fees, guideline-concordant supportive care medications) using Medicare reimbursement rates in January 2019. We used generalized estimating equations to estimate the association between NCCN EB measures and treatment cost with clustering at the level of the treatment indication. RESULTS: A total of 1,386 treatments were included. Among time-unlimited treatments (those administered on an ongoing basis without a predetermined stopping point), monthly cost was positively associated with efficacy ($3,036; 95% CI, $1,782 to $4,289) and quality of evidence ($1,509; 95% CI, $171 to $2,847) but negatively associated with safety (-$1,470; 95% CI, -$2,790 to -$151) and consistency of evidence (-$2,003; 95% CI, -$3,420 to -$586). Among time-limited treatments (those administered for a predetermined interval or number of cycles), no NCCN EB measure was significantly associated with treatment cost. CONCLUSIONS: An association between NCCN EB measures and treatment cost was inconsistent, and the magnitude of the association was small compared with the degree of cost variation among treatments with the same EB scores. The clinical value of cancer treatments does not seem to be a primary determinant of treatment cost.

Trends in Female Representation on NCCN Guideline Panels.

BACKGROUND: NCCN produces highly influential disease-specific oncology clinical practice guidelines. Because the number of women in academic oncology has increased, we assessed whether the composition of NCCN Guidelines Panels reflected this trend. METHODS: Using historical guidelines requested from NCCN, we investigated time trends for female representation on 21 NCCN Guidelines Panels and analyzed the trends for female-predominant cancers (breast, ovarian, uterine, and cervical) compared with all cancers. RESULTS: From 2013 to 2019, there was an increase from 123 women of 541 total panelists (22.7%) to 175 women of 542 panelists (32.3%). Within the 4 female-predominant cancers, the increase was more rapid: from 30 of 101 total panelists (29.7%) to 66 of 118 panelists (56.4%). Excluding female-predominant cancers, increases were minimal. CONCLUSIONS: There could be multiple explanations for these differing trends, including the possibility of more rapid increases in the underlying pool of female physician-scientists in female-predominant specialties or more efforts to increase the representation of women in decisions about the standard of care in cancers predominantly affecting women.

The Accuracy and Usefulness of the National Comprehensive Cancer Network Evidence Blocks Affordability Rating.

BACKGROUND: The National Comprehensive Cancer Network (NCCN) Guidelines' Evidence Blocks has the broadest scope of the several oncology value assessment frameworks. The Evidence Blocks includes the Affordability criterion, which reflects the financial cost of each treatment on a 1-5 scale. The accuracy of Affordability is unknown. METHODS: We calculated Medicare costs for all first-line and maintenance treatments for the 30 cancers with the highest incidence in the USA that had published NCCN Evidence Blocks as of 31 December 2018. We assessed the accuracy and consistency of Affordability across different treatments and cancer types. Among different treatments for the same indication, we determined the frequency with which the Affordability assessment was consistent with calculated treatment costs. RESULTS: There were a total of 1386 treatments in our sample. Lower Affordability scores were associated with higher costs. There was significant variation in cost at each level of Affordability; for treatments with Affordability = 1 (very expensive), costs ranged from $US4551 to $US43,794 per month for treatments administered over an undefined time period and from $US2865 to $US500,982 per course of therapy for treatments administered over a defined time period. Among treatments for the same indication, Affordability was discrepant with calculated treatment costs in 7.9% of pairwise comparisons, identifying the higher-cost treatment as being more affordable. Discrepancies were reduced when we reassigned Affordability scores based on calculated treatment costs. CONCLUSIONS: Evidence Blocks Affordability generally correlated with treatment costs but contained discrepancies, which may limit its usefulness to clinicians in comparing costs. This study suggests that the Affordability score may be improved by indexing more directly to specified dollar value thresholds.

Accurate estimation of cardiovascular risk in a non-diabetic adult: detecting and correcting the error in the reported Framingham Risk Score for the Systolic Blood Pressure Intervention Trial population.

OBJECTIVES: To understand the discrepancy between the published 10-year cardiovascular risk and 10-year cardiovascular risk generated from raw data using the Framingham Risk Score for participants in the Systolic Blood Pressure Intervention Trial (SPRINT). DESIGN: Secondary analysis of SPRINT data published in The New England Journal of Medicine (NEJM) and made available to researchers in late 2016. SETTING: SPRINT clinical trial sites. PARTICIPANTS: Study participants enrolled into SPRINT. RESULTS: The number of SPRINT study participants identified as having ≥15% 10-year cardiovascular risk was not consistent with what was reported in the original publication. Using the data from the trial, the Framingham Risk Score indicated ≥15% 10-year cardiovascular risk for 7089 participants compared with 5737 reported in the paper, a change from 61% to 76% of the total study population. CONCLUSIONS: The analysis of the clinical trial data by independent investigators identified an error in the reporting of the risk of the study population. The SPRINT trial enrolled a higher risk population than was reported in the initial publication, which was brought to light by data sharing.

Data Sharing and Cardiology: Platforms and Possibilities.

Sharing deidentified patient-level research data presents immense opportunities to all stakeholders involved in cardiology research and practice. Sharing data encourages the use of existing data for knowledge generation to improve practice, while also allowing for validation of disseminated research. In this review, we discuss key initiatives and platforms that have helped to accelerate progress toward greater sharing of data. These efforts are being prompted by government, universities, philanthropic sponsors of research, major industry players, and collaborations among some of these entities. As data sharing becomes a more common expectation, policy changes will be required to encourage and assist data generators with the process of sharing the data they create. Patients also will need access to their own data and to be empowered to share those data with researchers. Although medicine still lags behind other fields in achieving data sharing's full potential, cardiology research has the potential to lead the way.