The inflammation-based index can predict response and improve patient selection in NETs treated with PRRT: a pilot study
File(s)
Accepted version
Author(s)
Black, James
Atkinson, Stephen
Singh, Amal
Evans, joanne
Sharma, Rohini
Type
Journal Article
Abstract
Background
Peptide Receptor Radionuclide Therapy (PRRT) is an effective treatment for certain patients with metastatic neuroendocrine tumours (NETs). Tumour response is highly variable; no biomarker in clinical practice has been demonstrated to reliably predict outcome. The Inflammation-Based Index (IBI), derived from serum C-reactive protein and albumin levels, predicts survival and response to treatment in patients in a number of cancer types and was therefore explored in this setting.
Materials and Methods
Clinico-pathological data from patients undergoing PRRT for metastatic NETs were collected at baseline and during treatment. The primary endpoint was progression free survival (PFS) with a secondary endpoint of overall survival (OS). Cox regression analysis tested associations between baseline variables and their dynamic changes, and PFS and OS. Decision curve analysis (DCA) was used to determine the net benefit associated with a treatment strategy determined by the baseline IBI and non-response to PRRT.
Results
Fifty-five patients were recruited. Baseline IBI >0 was associated with inferior PFS (HR 14.2 (95% CI 5.25-38.5), p<0.001) and OS (p<0.001). Multivariate analysis confirmed an independent association between IBI and PFS (p=0.001). DCA indicated a net clinical benefit at risk thresholds between 0.03 and 0.58.
Conclusion
Baseline IBI score and its dynamic change through treatment are associated with both PFS and OS. At a risk threshold equivalent to the currently accepted rate of non-response to therapy, implementation of this easily derived score could avoid a significant number of futile treatments. These findings should be validated in additional independent cohorts.
Peptide Receptor Radionuclide Therapy (PRRT) is an effective treatment for certain patients with metastatic neuroendocrine tumours (NETs). Tumour response is highly variable; no biomarker in clinical practice has been demonstrated to reliably predict outcome. The Inflammation-Based Index (IBI), derived from serum C-reactive protein and albumin levels, predicts survival and response to treatment in patients in a number of cancer types and was therefore explored in this setting.
Materials and Methods
Clinico-pathological data from patients undergoing PRRT for metastatic NETs were collected at baseline and during treatment. The primary endpoint was progression free survival (PFS) with a secondary endpoint of overall survival (OS). Cox regression analysis tested associations between baseline variables and their dynamic changes, and PFS and OS. Decision curve analysis (DCA) was used to determine the net benefit associated with a treatment strategy determined by the baseline IBI and non-response to PRRT.
Results
Fifty-five patients were recruited. Baseline IBI >0 was associated with inferior PFS (HR 14.2 (95% CI 5.25-38.5), p<0.001) and OS (p<0.001). Multivariate analysis confirmed an independent association between IBI and PFS (p=0.001). DCA indicated a net clinical benefit at risk thresholds between 0.03 and 0.58.
Conclusion
Baseline IBI score and its dynamic change through treatment are associated with both PFS and OS. At a risk threshold equivalent to the currently accepted rate of non-response to therapy, implementation of this easily derived score could avoid a significant number of futile treatments. These findings should be validated in additional independent cohorts.
Date Issued
2019-02-01
Date Acceptance
2018-09-10
Citation
Journal of Clinical Endocrinology and Metabolism, 2019, 104 (1), pp.285-292
ISSN
0021-972X
Publisher
Oxford University Press (OUP)
Start Page
285
End Page
292
Journal / Book Title
Journal of Clinical Endocrinology and Metabolism
Volume
104
Issue
1
Copyright Statement
© 2018 Endocrine Society. This is a pre-copy-editing, author-produced version of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version is available online at: https://academic.oup.com/jcem/advance-article/doi/10.1210/jc.2018-01214/5095446
Sponsor
Imperial College Healthcare NHS Trust- BRC Funding
Grant Number
RDB01 79560
Subjects
1103 Clinical Sciences
1114 Paediatrics And Reproductive Medicine
Endocrinology & Metabolism
Publication Status
Published
Date Publish Online
2018-09-13