OBJECTIVE Sustained postoperative opioid use after elective surgery is a matter of growing concern. Herein, the authors investigated incidence and predictors of long-term opioid use among patients undergoing elective lumbar spine surgery, especially as a function of opioid prescribing practices at postoperative discharge (dose in morphine milligram equivalents [MMEs] and type of opioid). METHODS The OptumLabs Data Warehouse (OLDW) was queried for postdischarge opioid prescriptions for patients undergoing elective lumbar decompression and discectomy (LDD) or posterior lumbar fusion (PLF) for degenerative spine disease. Only patients who received an opioid prescription at postoperative discharge and those who had a minimum of 180 days of insurance coverage prior to surgery and 180 days after surgery were included. Opioid-naive patients were defined as those who had no opioid fills in 180 days prior to surgery. The following patterns of long-term postoperative use were investigated: additional fills (at least one opioid fill 90–180 days after surgery), persistent fills (any span of opioid use starting in the 180 days after surgery and lasting at least 90 days), and Consortium to Study Opioid Risks and Trends (CONSORT) criteria for persistent use (episodes of opioid prescribing lasting longer than 90 days and 120 or more total days’ supply or 10 or more prescriptions in 180 days after the index fill). Multivariable logistic regression was performed to identify predictors of long-term use. RESULTS A total of 25,587 patients were included, of whom 52.7% underwent PLF (n = 13,486) and 32.5% (n = 8312) were opioid-naive prior to surgery. The rates of additional fills, persistent fills, and CONSORT use were 47%, 30%, and 23%, respectively, after PLF and 35.4%, 19%, and 14.2%, respectively, after LDD. The rates among opioid-naive patients were 18.9%, 5.6%, and 2.5% respectively, after PLF and 13.3%, 2.0%, and 0.8%, respectively, after LDD. Using multivariable logistic regression, the following were identified to be significantly associated with higher risk of long-term opioid use following PLF: discharge opioid prescription ≥ 500 MMEs, prescription of a long-acting opioid, female sex, multilevel surgery, and comorbidities such as depression and drug abuse (all p < 0.05). Elderly (age ≥ 65 years) and opioid-naive patients were found to be at lower risk (all p < 0.05). Similar results were obtained on analysis for LDD with the following significant additional risk factors identified: discharge opioid prescription ≥ 400 MMEs, prescription of tramadol alone at discharge, and inpatient surgery (all p < 0.05). CONCLUSIONS In an analysis of pharmacy claims from a national insurance database, the authors identified incidence and predictors of long-term opioid use after elective lumbar spine surgery.
Reply: Adoption of Antifibrotic Medications: A Closer Look at the Data
Abstract Rationale In October 2014, the antifibrotic medications pirfenidone and nintedanib became the first medications approved by the U.S. Food and Drug Administration for use in patients with idiopathic pulmonary fibrosis (IPF). Since approval, there has been no nonregistry analysis of the real-world adoption of these medications in everyday clinical practice. Objectives To evaluate the adoption, persistence, and out-of-pocket (OOP) costs of pirfenidone and nintedanib since their approval in the United States in 2014. Methods A retrospective cohort analysis was performed by identifying privately insured and Medicare Advantage beneficiaries with IPF. We then split the patients into three cohorts: those who were untreated and those who filled a prescription for either pirfenidone or nintedanib between October 1, 2014, and July 31, 2019. The primary outcome was adoption of the medications. Secondary outcomes included medication persistence and prescription drug costs. Results A total of 10,996 patients with IPF were identified in the data set. A minority of patients (26.4%) with IPF identified in the cohort had started either medication since approval in 2014, with the adoption of both medications being comparable at around 13.2%. Those receiving the medications were younger (72 vs. 73.9 yr; P < 0.0001) and healthier (3.9 vs. 4.9 comorbidities; P < 0.0001) than those not receiving treatment. Men were significantly more likely to receive treatment than woman (30.0% vs. 21.9%; P < 0.0001). Among treated patients, 42.8% discontinued the medications during the study period. Patients’ OOP expenses per month were high for both drugs (mean, $397.51 for nintedanib; mean, $394.49 for pirfenidone). Conclusions The adoption of both the antifibrotic medications in the United States in everyday practice has been low since approval and may be associated with the high OOP cost.
Abstract P4-17-08: Surveillance mammography after treatment for male breast cancer
Abstract Background: The clinical utility of routine annual mammogram after curative-intent treatment for male breast cancer is uncertain. There is potentially greater value after lumpectomy (as surveillance for ipsilateral recurrence) than mastectomy (as screening for a new contralateral cancer). The goal of this study was to assess real world use of mammography in men during the first year after lumpectomy or mastectomy to treat breast cancer. Methods: Administrative claims data from OptumLabs Data Warehouse (a large US database that includes privately insured patients and Medicare Advantage-insured enrollees from all 50 states and of all ages and ethnic and racial groups) were used to identify men treated with breast surgery for a new diagnosis of breast cancer between 2007 and 2017. We required continuous coverage starting at least 6 months prior to the non-metastatic breast cancer diagnosis and continuing until at least 13 months after the breast surgery. Our primary endpoint was the proportion of patients who had at least one mammogram during the year (13-month period, to allow for scheduling and other logistical delays) after lumpectomy or mastectomy. Univariate and multivariate testing were performed to identify predictors of mammography (with p<0.05 used as the threshold for statistical significance for both). Our secondary endpoint was the proportion with at least one mammogram within 24 months of surgery, performed in a subset who maintained their insurance coverage for at least that duration. Results: The 13-month analysis included 730 men with a median age at diagnosis of 62 years (Range: 25 to 87 years) and a median follow-up duration of 35 months (Range: 13 to 134 months). 209 (29%) of these men underwent mammography within 13 months after surgery. The characteristics of patients who underwent mammography and those who did not are shown in Table 1. Mammography was more likely after lumpectomy than mastectomy (41% vs. 27%) and after radiation therapy (41% vs. 32% in those who did not receive radiation). In a multivariate logistic regression model, more recent diagnosis (2015+) was associated with lower odds of undergoing mammography, while receipt of radiation was associated with higher odds of undergoing mammography. In the subset of patients with two or more years of post-surgery coverage (n=527), the proportion who had at least one mammogram during that 24-month period was 49% after lumpectomy and 40% after mastectomy. Conclusions: In this insured cohort, 73% of men did not undergo mammography within a year after mastectomy, and 59% did not within a year after lumpectomy. Mammography was less likely in patients diagnosed more recently (perhaps due to acknowledgment of the unique aspects of male breast cancer including a relatively low risk of contralateral second primary tumors), and more likely in those who received radiation. These variations in practice likely result from the paucity of evidence-based guidelines for male breast cancer survivorship care. More research is needed pertaining to whether or not mammograms improve clinical outcomes after curative intent treatment for male breast cancer. Table 1: Patient characteristics associated with receipt of mammogram within first 13 months after male breast cancer surgeryUnivariate AnalysisMultivariate AnalysisNo Mammogram (N=521)Mammogram (N=209)P-value, chi-square testOdds Ratio (OR) and 95% CIP-value for ORAge Group:0.1225-4966 (12.7%)32 (15.3%)Reference50-64216 (41.5%)98 (46.9%)0.99 (0.60, 1.63)0.9665-74112 (21.5%)44 (21.1%)0.87 (0.48, 1.57)0.6575+127 (24.4%)35 (16.7%)0.57 (0.30, 1.07)0.08Census Region:0.52Midwest138 (26.5%)59 (28.2%)ReferenceNortheast97 (18.6%)47 (22.5%)1.10 (0.68, 1.78)0.69South223 (42.8%)79 (37.8%)0.74 (0.49, 1.11)0.15West63 (12.1%)24 (11.5%)0.83 (0.47, 1.47)0.51Year of diagnosis:0.072007-2010126 (24.2%)65 (31.1%)Reference2011-2014199 (38.2%)82 (39.2%)0.80 (0.54, 1.20)0.292015+196 (37.6%)62 (29.7%)0.63 (0.41, 0.96)0.03Elixhauser Category:0.250148 (28.4%)69 (33.0%)Reference1-2218 (41.8%)74 (35.4%)0.85 (0.56, 1.28)0.433+155 (29.8%)66 (31.6%)1.18 (0.75, 1.87)0.47Surgery Type:0.005Lumpectomy55 (10.6%)38 (18.2%)ReferenceMastectomy466 (89.4%)171 (81.8%)1.57 (0.97, 2.55)0.07Chemotherapy:0.79No301 (57.8%)123 (58.9%)ReferenceYes220 (42.2%)86 (41.1%)0.79 (0.54, 1.16)0.23Radiation:0.02No355 (68.1%)124 (59.3%)ReferenceYes166 (31.9%)85 (40.7%)1.51 (1.03, 2.20)0.03 Citation Format: Siddhartha Yadav, Lindsey Sangaralingham, Stephanie R. Payne, Karthik V. Giridhar, Tina J. Hieken, Judy C. Boughey, Robert W. Mutter, John R. Hawse, Rafael E. Jimenez, Rachel A. Freedman, Sadia Choudhery, Fergus J. Couch, Celine M. Vachon, Nilay Shah, Roberto A. Leon-Ferre, Kathryn J. Ruddy. Surveillance mammography after treatment for male breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-17-08.
Patterns of Use, Efficacy, and Safety of Treatment Options for Patients with Graves' Disease: A Nationwide Population-Based Study