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Tumor response assessment: comparison between unstructured free text reporting in routine clinical workflow and computer-aided evaluation based on RECIST 1.1 criteria

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Purpose: Standardized computer-aided tumor response assessment is common in clinical trials. In contrast, unstructured free text reporting (UFTR) is common in daily routine. Therefore, this study aimed to discern and quantify differences between UFTR and computer-aided standardized tumor response evaluation based on RECIST 1.1 criteria (RECIST), serving as gold standard, in clinical workflow. Methods: One-hundred consecutive patients with cancer eligible for RECIST 1.1 evaluation, who received five follow-up CTs of the trunk, were retrospectively included. All UFTRs were assigned to RECIST response categories [complete response, partial response (PR), stable disease (SD), progressive disease (PD)]. All CTs were re-evaluated using dedicated software (mint lesion™) applying RECIST 1.1. The accordance in tumor response ratings was analyzed using Cohen's kappa. Results: At the first follow-up, 47 cases were rated differently with an SD underrepresentation and a PR and PD overrepresentation in UFTR. In the subsequent follow-ups, categorical differences were seen in 38, 44, 37, and 44%. Accordance between UFTR and RECIST was fair to moderate (Cohen's kappa: 0.356, 0.477, 0.390, 0.475, 0.376; always p < 0.001). Differences were mainly caused by the rating of even small tumor burden changes as PD or PR in UFTR or by comparison to the most recent prior CT scan in UFTR instead of comparison to nadir or baseline. Conclusions: Significant differences in tumor response ratings were detected comparing UFTR and computer-aided standardized evaluation based on RECIST 1.1. Thus, standardized reporting should be implemented in daily routine workflow.
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J Cancer Res Clin Oncol (2017) 143:2527–2533
DOI 10.1007/s00432-017-2488-1
ORIGINAL ARTICLE – CLINICAL ONCOLOGY
Tumor response assessment: comparison betweenunstructured
free text reporting inroutine clinical workflow
andcomputer‑aided evaluation based onRECIST 1.1 criteria
JulianeGoebel1 · JuliaHoischen2· CarolinGramsch3· HaemiP.Schemuth1·
Andreas‑ClaudiusHoffmann4· LaleUmutlu1· KaiNassenstein1
Received: 7 May 2017 / Accepted: 1 August 2017 / Published online: 19 August 2017
© Springer-Verlag GmbH Germany 2017
moderate (Cohen’s kappa: 0.356, 0.477, 0.390, 0.475, 0.376;
always p<0.001). Differences were mainly caused by the
rating of even small tumor burden changes as PD or PR in
UFTR or by comparison to the most recent prior CT scan in
UFTR instead of comparison to nadir or baseline.
Conclusions Significant differences in tumor response rat-
ings were detected comparing UFTR and computer-aided
standardized evaluation based on RECIST 1.1. Thus, stand-
ardized reporting should be implemented in daily routine
workflow.
Keywords Oncologic imaging· Radiological tumor
response assessment· RECIST 1.1 criteria·
Cross-sectional imaging· Solid tumors
Introduction
The assessment of tumor burden change is important in
the evaluation of cancer therapeutics in clinical trials as
well as in therapy monitoring in daily clinical routine.
The use of tumor shrinkage as an objective parameter for
tumor response in cancer therapy is based on the evidence
that for many solid tumors, a decrease in tumor burden is
associated with an improved patient survival (Paesmans
etal. 1997; Buyse etal. 2000; El-Maraghi and Eisenhauer
2008) and the fact that clinical symptoms may often be
misleading especially in advanced solid tumors or in
aggressive therapy regimens. Other surrogate markers like
serum tests (so-called tumor markers, C-reactive protein,
lactate dehydrogenase) may be useful (Fang etal. 2015;
Scartozzi etal. 2012); however, the objective change in
tumor burden is considered to be the backbone of deci-
sion making in clinical trials as well as in clinical routine.
Cross-sectional imaging either by computed tomography
Abstract
Purpose Standardized computer-aided tumor response
assessment is common in clinical trials. In contrast, unstruc-
tured free text reporting (UFTR) is common in daily rou-
tine. Therefore, this study aimed to discern and quantify
differences between UFTR and computer-aided standardized
tumor response evaluation based on RECIST 1.1 criteria
(RECIST), serving as gold standard, in clinical workflow.
Methods One-hundred consecutive patients with can-
cer eligible for RECIST 1.1 evaluation, who received five
follow-up CTs of the trunk, were retrospectively included.
All UFTRs were assigned to RECIST response categories
[complete response, partial response (PR), stable disease
(SD), progressive disease (PD)]. All CTs were re-evaluated
using dedicated software (mint lesion™) applying RECIST
1.1. The accordance in tumor response ratings was analyzed
using Cohen’s kappa.
Results At the first follow-up, 47 cases were rated dif-
ferently with an SD underrepresentation and a PR and PD
overrepresentation in UFTR. In the subsequent follow-
ups, categorical differences were seen in 38, 44, 37, and
44%. Accordance between UFTR and RECIST was fair to
* Juliane Goebel
Juliane.Goebel@uk-essen.de
1 Department ofDiagnostic andInterventional Radiology
andNeuroradiology, University Hospital Essen,
Hufelandstrasse 55, 45122Essen, Germany
2 Department ofRadiology, Evangelic Hospital Duesseldorf,
Duesseldorf, Germany
3 Institute forNeuroradiology, University Hospital Giessen,
Giessen, Germany
4 Department ofOncology andHematology, Helios Hospital
Ahrenshoop, Ahrenshoop, Germany
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... For the survival of patients, it is crucial that radiological treatment monitoring provides substantial information for therapeutic decision making. However, a recent study suggests that the value of radiologic reports considerably depends on the methodical approach of assessment (Goebel et al. 2017). ...
... In parallel, we imported the same image datasets into a commercially available semi-automatic software (mint lesion version 3.7.3, MINT Medical GmbH) (Goebel et al. 2017). A radiologist with 13 years of experience, blinded to FTRs, retrospectively selected target lesions for baseline entries. ...
... A previous trial on tumors of various origins (Goebel et al. 2017) reported on fair to moderate agreement between FTR and RECIST 1.1 based reports. In most cases, different reporting with FTR was attributed to assignment of even minor changes in tumor burden to PR or PD instead of SD. a Non-clear cell RCC: papillary RCC, collecting duct RCC b IMDC prognostic risk was rated as follows: 0 risk factors, favorable; 1-2 risk factors, intermediate; ≥ 3 risk factors, poor (Motzer et al. 2019) c No cancer cells seen microscopically at the primary tumor site d Nuclear grading system based on microscopic morphology, which evaluates nuclear size, shape, and nucleolar prominence e T stage describes the size and extent of the primary tumor (Lam et al. 2009) Content courtesy of Springer Nature, terms of use apply. ...
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... 1) The radiologist oversees both manual completion of the CRF and drafts the UFTR. This workflow is the most time-consuming and, for the above-mentioned reasons, mismatches often occur between CRF and transcriptions from voice recordings [16]. Moreover, one or other or both of these reports can contain mistakes. ...
... In the event of inconsistencies, the radiologist must repeat the procedure thus losing the initial time-saving benefit. Moreover, this data-mining procedure can result in misevaluations in the event of missing data (forgotten by the radiologist), of a misunderstanding of the UFTR, or of transcription errors [16]. ...
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