Sarah Huepenbecker

Real-world use of immune checkpoint inhibitors in advanced or recurrent endometrial cancer

The aim of this study was to describe real-world use of immune checkpoint inhibitors for women with advanced or recurrent endometrial cancer. Adult women with advanced or recurrent endometrial cancer who received at least one line of systemic treatment between January 1, 2014 and November 1, 2020, then followed to May 31, 2021 in a nationwide electronic health record-derived de-identified database. Chi-Squared test or Welch's 2-sample t-tests were used to compare patient and clinical factors associated with immune checkpoint inhibitor treatment. Time to next treatment analyses were performed based on the treatment line of the immune checkpoint inhibitor. Sankey plots depicted patient-level temporal systemic treatment. During our study period, 326 women received their first immune checkpoint inhibitor treatment, increasing from 12 patients in 2016 to 148 in 2020. Factors associated with ever receiving immune checkpoint inhibitors included disease stage (p=0.002), mismatch repair (MMR)/microsatellite instability (MSI) status (p<0.001), performance status (p=0.001), and prior radiation receipt (p<0.001) and modality (p=0.003). The most common immune checkpoint inhibitor regimen was pembrolizumab (47.9%) followed by pembrolizumab and lenvatinib (34.7%). Immune checkpoint inhibitors were given as first, second, and third or greater lines of therapy in 24.5%, 41.7%, and 46.1% of evaluable patients. The median time to next treatment was significantly longer if given as an earlier line of treatment (p=0.008). There were significant differences in treatment line of immune checkpoint inhibitor by region (p=0.004), stage (p<0.001), and prior radiation receipt (p=0.014) and modality (p=0.009). Among 326 patients who received immune checkpoint inhibitors, 114 (34.9%) received subsequent treatment including chemotherapy (43.9%), additional immune checkpoint inhibitors (29.8%), and other (26.3%) with no differences in demographic or clinical characteristics based on the type of post-immune checkpoint inhibitor treatment. In an observational retrospective real-world database study, immune checkpoint inhibitors were used in 14.7% of patients with advanced or recurrent endometrial cancer across multiple lines of treatment, including after initial immune checkpoint inhibitor treatment.

Factors impacting the time to ovarian cancer diagnosis based on classic symptom presentation in the United States

BackgroundPatients with ovarian cancer often present with late‐stage disease and nonspecific symptoms, but little is known about factors affecting the time to diagnosis (TTD) in the United States.MethodsA retrospective, population‐based study of the Surveillance, Epidemiology, and End Results–Medicare database was conducted. It included women 66 years old or older with stage II to IV epithelial ovarian cancer with at least 1 code for abdominal/pelvic pain, bloating, difficulty eating, or urinary symptoms within 1 year of the cancer diagnosis. TTD was defined from the first claim with a prespecified symptom to the ovarian cancer diagnosis. Kruskal‐Wallis tests were used to assess for differences in TTD by group medians. Univariate and generalized linear models with a log‐link function evaluated TTD by covariables.ResultsFor the 13,872 women analyzed, the mean and median times to diagnosis were 2.9 and 1.1 months, respectively. The median TTD differed significantly by first symptom (P &lt; .001), number of symptoms (P &lt; .001), and first physician specialty seen (P &lt; .001). In a multivariable analysis, TTD differed significantly according to race/ethnicity (P &lt; .001), geographic region (P = .001), urban‐rural location (P = .031), emergency room presentation (P &lt; .001), and number of specialties seen (P &lt; .001). A shorter TTD was associated with a diagnosis in 2006‐2010 (relative risk [RR], 0.92; 95% confidence interval [CI], 0.87‐0.98) or 2011‐2015 (RR, 0.87; 95% CI, 0.81‐0.93) in comparison with 1992‐1999.ConclusionsThe time from a symptomatic presentation to care to a diagnosis of ovarian cancer is influenced by clinical and demographic variables. This study's findings reinforce the importance of educating all physicians on ovarian cancer symptoms to aid in diagnosis.Lay Summary Ovarian cancer is often diagnosed once disease has spread because the classic symptoms of ovarian cancer—abdominal or pelvic pain, bloating, difficulty eating, and urinary issues—can be mistaken for other problems. This study examined the time between when women with classic ovarian cancer symptoms went to a physician and when they received a cancer diagnosis in a large database population. The authors found that the time to diagnosis differed according to the type and number of symptoms and what type of physician a woman saw as well as factors such as race, geographic location, and year of diagnosis.

Association between time to diagnosis, time to treatment, and ovarian cancer survival in the United States

Evaluate the association between time to diagnosis and treatment of advanced ovarian cancer with overall and ovarian cancer specific mortality using a retrospective cross sectional study of a population based cancer registry database. The Surveillance, Epidemiology, and End Results-Medicare database was searched from 1992 to 2015 for women aged ≥66 years with epithelial ovarian cancer and abdominal/pelvic pain, bloating, difficulty eating, or urinary symptoms within 1 year of cancer diagnosis. Time from presentation to diagnosis and treatment were evaluated as outcomes and covariables. Cox regression models and adjusted Kaplan-Meier curves evaluated 5 year overall and cancer-specific survival. Among 13 872 women, better survival was associated with longer time from presentation to diagnosis (overall survival hazard ratio (HR) 0.95, 95% confidence interval (CI) 0.94 to 0.95; cancer specific survival HR 0.95, 95% CI 0.94 to 0.96) and diagnosis to treatment (overall survival HR 0.94, 95% CI 0.92 to 0.96; cancer specific survival HR 0.93, 95% CI 0.91 to 0.96). There was longer time from presentation to diagnosis in Hispanic women (relative risk (RR) 1.21, 95% CI 1.12 to 1.32) and from diagnosis to treatment in non-Hispanic black women (RR 1.36, 95% CI 1.21 to 1.54), with lower likelihood of survival at 5 years after adjustment for time to diagnosis and treatment among non-Hispanic black women (HR 1.15, 95% CI 1.05 to 1.26) compared with non-Hispanic white women. Gynecologic oncology visit was associated with improved overall (p<0.001) and cancer specific (p<0.001) survival despite a longer time from presentation to treatment (p<0.001). Longer time to diagnosis and treatment were associated with improved survival, suggesting that tumor specific features are more important prognostic factors than the time interval of workup and treatment. Significant sociodemographic disparities indicate social determinants of health influencing workup and care. Gynecologic oncologist visits were associated with improved survival, highlighting the importance of appropriate referral for suspected ovarian cancer.

Temporal trends of healthcare system use between symptomatic presentation and ovarian cancer diagnosis in the United States

To describe trends in healthcare system use over time between onset of classic ovarian cancer symptoms and ovarian cancer diagnosis in the United States. A population-based study of the Surveillance, Epidemiology, and End Results-Medicare database was conducted on patients aged ≥66 years with stage II-IV epithelial ovarian cancer between 1992 and 2015 with at least one of the following diagnosis codes: abdominal pain, bloating, difficulty eating, and/or urinary symptoms. The outcomes were frequency of visit type, frequency of diagnostic modality, and Medicare reimbursement between first symptomatic claim and cancer diagnosis. Jonckheere-Terpstra and Cochran-Armitage tests were used to evaluate trends over time. Among 13 872 women, 13 541 (97.6%) had outpatient, 6466 (46.6%) had inpatient, and 4906 (35.4%) had emergency room visits. The frequency of outpatient (p<0.001) and emergency room visits (p<0.001) increased while the frequency of inpatient visits (p<0.001) decreased between 1992 and 2015. The median number of outpatient visits (p<0.001) and physician specialties seen (p<0.001) increased over time. The median hospital length of stay decreased from 10 days in 1992 to 5 days in 2015 (p<0.001). Between 1992 and 2015, the frequency of ultrasound decreased (p<0.001) while the frequency of computed tomography, magnetic resonance imaging, positron emission tomography imaging, and cancer antigen 125 tumor immunoassay increased (p<0.001). Median monthly total (p<0.001), inpatient (p<0.001), and outpatient (p=0.006) reimbursements decreased while emergency room reimbursements increased (p<0.001) over time. Healthcare reimbursement between symptomatic presentation and ovarian cancer diagnosis has decreased over time and may reflect the trends in fewer and shorter hospitalizations and increased use of emergency and outpatient management during the evaluation of symptoms of women with ovarian cancer.

Algorithm to Identify Incident Epithelial Ovarian Cancer Cases Using Claims Data

PURPOSE To create an algorithm to identify incident epithelial ovarian cancer cases in claims-based data sets and evaluate performance of the algorithm using SEER-Medicare claims data. METHODS We created a five-step algorithm on the basis of clinical expertise to identify incident epithelial ovarian cancer cases using claims data for (1) ovarian cancer diagnosis, (2) receipt of platinum-based chemotherapy, (3) no claim for platinum-based chemotherapy but claim for tumor debulking surgery, (4) removed cases with nonplatinum chemotherapy, and (5) removed patients with prior claims with personal history of ovarian cancer code to exclude prevalent cases. We evaluated algorithm performance using SEER-Medicare claims data by creating four cohorts: incident epithelial ovarian cancer, a 5% random sample of cancer-free Medicare beneficiaries, a 5% random sample of incident nonovarian cancer, and prevalent ovarian cancer cases. RESULTS Using SEER tumor registry data as the gold standard, our algorithm correctly classified 89.9% of incident epithelial ovarian cancer cases (cohort n = 572) and almost 100% of cancer-free controls (n = 97,127), nonovarian cancer (n = 714), and prevalent ovarian cancer cases (n = 3,712). The overall algorithm sensitivity was 89.9%, the positive predictive value was 93.8%, and the specificity and negative predictive value were &gt; 99.9%. Patients were more likely to be correctly classified as incident ovarian cancer if they had stage III or IV disease compared with early stage I or II disease (93.5% v 83.7%, P &lt; .01), and grade 1-4 compared with unknown grade tumors (93.8% v 81.4%, P &lt; .01). CONCLUSION Our algorithm correctly identified most incident epithelial ovarian cancer cases, especially those with advanced disease. This algorithm will facilitate research in other claims-based data sets where cancer registry data are unavailable.