Erschienen in:
01.09.2015 | Nuclear Medicine
Nomogram including pretherapeutic parameters for prediction of
survival after SIRT of hepatic metastases from colorectal cancer
verfasst von:
Wolfgang Peter Fendler, Harun Ilhan, Philipp M. Paprottka, Tobias F. Jakobs, Volker Heinemann, Peter Bartenstein, Feras Khalaf, Samer Ezziddin, Marcus Hacker, Alexander R. Haug
Erschienen in:
European Radiology
|
Ausgabe 9/2015
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Abstract
Objectives
Pre-therapeutic prediction of outcome is important for clinicians
and patients in determining whether selective internal radiation therapy (SIRT)
is indicated for hepatic metastases of colorectal cancer (CRC).
Methods
Pre-therapeutic characteristics of 100 patients with colorectal
liver metastases (CRLM) treated by radioembolization were analyzed to develop a
nomogram for predicting survival. Prognostic factors were selected by univariate
Cox regression analysis and subsequent tested by multivariate analysis for
predicting patient survival. The nomogram was validated with reference to an
external patient cohort (n = 25) from the
Bonn University Department of Nuclear Medicine.
Results
Of the 13 parameters tested, four were independently associated with
reduced patient survival in multivariate analysis. These parameters included no
liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5× upper
limit of normal (HR:2.82, p = 0.001), and
summed computed tomography (CT) size of the largest two liver lesions ≥10 cm
(HR:2.31, p < 0.001). The area under the
receiver-operating characteristic curve for our prediction model was 0.83 for
the external patient cohort, indicating superior performance of our multivariate
model compared to a model ignoring covariates.
Conclusions
The nomogram developed in our study entailing four pre-therapeutic
parameters gives good prediction of patient survival post SIRT.
Key Points
• Four individual parameters predicted
reduced survival following SIRT in CRC.
• These parameters were combined into a
nomogram of pre-therapeutic risk stratification.
• The model provided good prediction of
survival in two independent patient cohorts.