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Improving the prognostic ability of PET/CT SUVmax to identify follicular lymphoma with early treatment failure
- Source :
- Am J Cancer Res
- Publication Year :
- 2022
- Publisher :
- e-Century Publishing Corporation, 2022.
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Abstract
- Follicular lymphoma (FL) has a high degree of heterogeneity both clinically and molecularly. Early treatment failure (ETF), progression or relapse within 24 months of frontline immunochemotherapy is associated with a poor prognosis in FL. However, the clinical utility of ETF at diagnosis is limited. The maximum standardized uptake value (SUVmax) is a metabolic parameter for positron emission tomography/computed tomography (PET/CT); nevertheless, the relationship between SUVmax and ETF remains unclear. Thus, identifying early biomarkers that incorporate SUVmax and other clinical correlative variables could be helpful in identifying patients at high risk of ETF. A nomogram consisted of three independent variables, including SUVmax ≥ 12, beta-2 microglobulin > 3 mg/L, and Ki67 > 40%, was established to predict ETF in 127 patients with grade 1, 2, or 3a FL from the First Hospital of Jilin University (training cohort) and was validated using data from the Duke University Medical Center (validation cohort, n=95). The nomogram demonstrated prognostic accuracy in predicting ETF (sensitivity 70.8% and specificity 83.5% in the training cohort; sensitivity 84.2% and specificity 68.4% in the validation cohort). The patients were stratified into three groups: low-, intermediate-, and high-risk. In the training cohort, the corresponding 5-year progression-free survival (PFS) rates were 81.7%, 73.4%, and 34.9%, and the 5-year overall survival (OS) rates were 97.4%, 87.4%, and 62.3%, respectively. In the validation cohort, the 5-year PFS rates were 77.7%, 52.9%, and 34.8%, and the 5-year OS rates were 96.4%, 94.1%, and 73.7%, respectively. This was the first study to use a nomogram with SUVmax to predict ETF in FL to identify a subset of patients who might benefit from individualized targeted therapy.
- Subjects :
- Original Article
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Am J Cancer Res
- Accession number :
- edsair.pmid..........b3d31834eb24869ed879ab145fe91d6e