ABSTRACT
CASE: A 31-year-old man with a history of giant cell tumor of bone (GCTB) in the distal radius presents to clinic 9 years after en bloc distal radius resection. He was found to have a new soft tissue mass consistent with GCTB and new pulmonary metastases. Ultimately, he underwent excision of his soft tissue recurrence and partial lobectomy for his lung metastases. CONCLUSION: This case highlights the importance of having a high level of suspicion for local recurrence or metastasis, even years after wide resection and negative margins.
Subject(s)
Bone Neoplasms , Giant Cell Tumor of Bone , Lung Neoplasms , Male , Humans , Adult , Radius/surgery , Giant Cell Tumor of Bone/diagnostic imaging , Giant Cell Tumor of Bone/surgery , Lung Neoplasms/surgery , Bone Neoplasms/diagnostic imaging , Bone Neoplasms/surgeryABSTRACT
PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.
