Imperial College London
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ProfessorRohiniSharma

Faculty of Medicine, Department of Surgery & Cancer

Professor Clinical Pharmacology and Medical Oncology
 
 
 
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Contact

 

+44 (0)20 3313 3059r.sharma Website

 
 
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Location

 

ICTEM buildingHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Black:2019:10.1210/jc.2018-01214,
author = {Black, J and Atkinson, S and Singh, A and Evans, J and Sharma, R},
doi = {10.1210/jc.2018-01214},
journal = {Journal of Clinical Endocrinology and Metabolism},
pages = {285--292},
title = {The inflammation-based index can predict response and improve patient selection in NETs treated with PRRT: a pilot study},
url = {http://dx.doi.org/10.1210/jc.2018-01214},
volume = {104},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundPeptide 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 MethodsClinico-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.ResultsFifty-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.ConclusionBaseline 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.
AU  - Black,J
AU  - Atkinson,S
AU  - Singh,A
AU  - Evans,J
AU  - Sharma,R
DO  - 10.1210/jc.2018-01214
EP  - 292
PY  - 2019///
SN  - 0021-972X
SP  - 285
TI  - The inflammation-based index can predict response and improve patient selection in NETs treated with PRRT: a pilot study
T2  - Journal of Clinical Endocrinology and Metabolism
UR  - http://dx.doi.org/10.1210/jc.2018-01214
UR  - http://hdl.handle.net/10044/1/64646
VL  - 104
ER  -
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