Prevalence of hypercalcemia among cancer patients in the United States.

Hypercalcemia of malignancy (HCM) is a serious metabolic complication whose population-based prevalence has not been quantified. Rates of HCM differ by tumor type, with highest rates reported in multiple myeloma and lowest among colorectal and prostate cancer patients. This analysis estimates HCM prevalence in the US. This retrospective study used the Oncology Services Comprehensive Electronic Records (OSCER) warehouse of electronic health records (EHR) including laboratory values from 569000 patients treated at 565 oncology outpatient sites. OSCER data were projected to the national level by linking EHR to claims data. Cancer patients included were ≥18 years, and had serum calcium (Ca) and albumin (for corrected serum Ca [CSC]) records. Period prevalence was estimated by HCM CTCAE grade, tumor type, and year (2009-2013). Estimates were adjusted to capture patients diagnosed with HCM outside oncology practices based on a subset of patients linkable to office and hospital data. The analysis included 68023 (2009) to 121482 (2013) cancer patients. In 2013, patients with HCM had a median of six Ca tests, 69.7% had chemotherapy, and 34% received bone modifying agents. HCM rates were highest for multiple myeloma patients (7.5% [2012]-10.2% [2010]), lowest for prostate cancer (1.4% [2012]-2.1% [2011]).The estimated adjusted annual prevalence of HCM from 2009 to 2013 was 95441, 96281, 89797, 70158, and 71744, respectively. HCM affected 2.0-2.8% of all cancer patients. EHR data from oncology clinics were critical for this study because these data contain results from laboratory studies (i.e., serum calcium values) that are routinely ordered in that setting. We estimated that the prevalence of HCM in the US in 2013 is 71744, affecting approximately 2% of cancer patients overall. This percentage differs by tumor type and appears to have decreased over the five-year study period.

Real-World Axitinib Use in the United States: A Retrospective Study Using Linked Datasets.

BACKGROUND: Axitinib is approved by the FDA for the treatment of advanced renal cell carcinoma (RCC) after failure of 1 previous systemic therapy and is distributed primarily through specialty pharmacies. Although the efficacy and safety of axitinib have been established in clinical trials, information from real-world populations will help to elucidate patients' clinical profiles and utilization patterns. Prescription records alone provide limited information on patient characteristics and other treatment experiences. Expansion of these data with information from medical claims databases should yield observational real-world data that may help to optimize therapy for patients with advanced RCC. OBJECTIVE: To link information from a specialty pharmacy database with information from medical and pharmacy claims databases to characterize real-world treatment patterns of axitinib as subsequent systemic therapy in patients with RCC in the United States. METHODS: This retrospective, observational, cohort study linked de-identified patient-level data from 22 specialty pharmacies that dispense axitinib with databases of longitudinal medical and pharmacy claims. Eligible patients had a diagnosis of RCC (> 1 claim for RCC defined as ICD-9-CM code 189.0), previously received > 1 systemic therapy, had the first prescription for axitinib dispensed between May 2012 and April 2013 (index), and had consistent claims reporting by pharmacies and physicians. All treatment data were used to calculate cycle, line of therapy, and duration of therapy; prescription data were used to determine axitinib dose modifications. Multivariate and logistic regression analyses were conducted to assess the effect of patient/prescriber characteristics on duration of axitinib therapy and dose modifications, respectively. RESULTS: In all, 1,175 patients met the study inclusion criteria and had data present in specialty pharmacy and claims databases. Most patients (74%) were male, and 68% were aged 55-74 years. Mean (SD) Charlson Comorbidity Index score was 2.7 (± 1.1); the most common comorbidity was hypertension (in 199 patients, 17%). Based on Rx-Risk-V, the most frequent concomitant conditions were pain (40%) and ischemic heart disease/hypertension (30%); the most frequent concomitant medications were antihypertensive medications (46%) and opiates (40%). Most prescribers (63%) were affiliated with an academic center, and all U.S. geographic regions were represented. In all, 847 patients (72%) had commercial insurance. Axitinib was prescribed as second-line therapy in 659 patients (56%), as third-line therapy in 326 patients (28%), and as fourth-line or later therapy in 190 patients (16%). In the overall population, mean (SD) duration of axitinib therapy was 168.6 (± 148.4) days. Axitinib treatment duration was 21 days longer in males than females (P = 0.013); 28 days longer in patients in the Northeast than in the Midwest or West (P = 0.010 and P = 0.016, respectively); and 26 days longer in patients receiving baseline hypothyroidism treatment (P = 0.004). In patients receiving second-line axitinib, the most common first-line therapy was sunitinib (56%), followed by pazopanib (16%) and everolimus (12%). Mean (SD) duration of second-line axitinib treatment was 172.3 (± 150.6) days and ranged from 127 days in patients who previously received temsirolimus to 196 days in those who previously received sorafenib. Of 1,025 patients who initiated axitinib at the standard 5 mg twice daily starting dose, 70% remained at this dose throughout treatment, whereas 10% had a dose increase. Younger age and gender (male) were associated with dose increases (OR = 0.958, 95% CI = 0.941-0.975 and OR = 0.573, 95% CI = 0.364-0.903, respectively). Baseline hypothyroidism treatment was associated with dose decreases and increases (OR = 1.662, 95% CI = 1.088-2.539 and OR = 2.149, 95% CI = 1.353-3.413, respectively). CONCLUSIONS: This analysis demonstrates the feasibility and utility of linking specialty pharmacy data to other longitudinal databases to better understand patient, provider, and reimbursement characteristics. These data provide insight into routine clinical use of axitinib as subsequent RCC therapy in the United States in the period following FDA approval, as well as additional information on sequencing of targeted agents in patients with advanced RCC. DISCLOSURES: This study was sponsored by Pfizer. MacLean and Cisar are employees of and hold stock in Pfizer. At the time of this analysis, Mehle, Eremina, and Quigley were employees of IMS Health who were paid consultants to Pfizer during the conduct of this study and in connection with the development of this manuscript. MacLean and Cisar contributed to study design and manuscript development. Mehle, Eremina, and Quigley contributed to study design, analysis, and manuscript development.

Where your data is going and where it's been.

Collecting data is time-consuming and expensive. Electronic transactions, including electronic medical records and the unification of many billing procedures, have transformed the rate at which data are able to be extracted. Although obstacles remain, the rate at which data are de-identified, collected, and aggregated will help improve safety and standards of care for oncology patients. Everyone participating in the care of oncology patients must understand how important data are as the quality initiatives and performance metrics are numerous and growing; these initiatives cannot be successful without timely, accurate, and quantifiable data that address the continuum of oncology care.