Literature DB >> 35345060

Research Highlight: How to Use Technical and Oncologic Outcomes of Image-Guided Tumor Ablation According to Guidelines by Society of Interventional Oncology and DATECAN?

Min Woo Lee1,2, Hyunchul Rhim1,3.   

Abstract

Entities:  

Keywords:  Guideline; Image-guided ablation; Recurrence; Survival; Tumor

Mesh:

Year:  2022        PMID: 35345060      PMCID: PMC8961014          DOI: 10.3348/kjr.2021.0982

Source DB:  PubMed          Journal:  Korean J Radiol        ISSN: 1229-6929            Impact factor:   3.500


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Take-home points

• We highlight key points from recent consensus guidelines by Society of Interventional Oncology (SIO) and Definition for the Assessment of Time-to-event Endpoints in CANcer trials (DETACAN) to facilitate effective communication in the field of image-guided tumor ablation. • The guidelines include recommendations for defining and analyzing various oncologic endpoints at per-patient, per-procedure, or per-tumor levels and terminologies commonly used in image-guided tumor ablation. • Precise definitions of various oncologic endpoints and terminologies will lead to an objective and reliable interpretation of results and accurate comparison of oncologic outcomes of image-guided tumor ablation, ultimately providing scientific reproducibility among researchers. To ensure a standardized interpretation and reporting of results and allow for accurate comparison of image-guided tumor ablation outcomes, the SIO and DATECAN group recently published consensus guidelines [1]. We want to highlight some key points, to facilitate their use in reporting and reviewing research studies.

Background of Guideline Development

In 2014, Ahmed et al. [2] published a paper regarding the updated standardized terminology and reporting criteria for image-guided tumor ablation, which has been cited by over 500 studies on tumor ablation over the past eight years. The document has contributed to interventional oncology by providing a common language to describe the treatments and their outcomes and has facilitated effective communication throughout the field. However, there is still variability in interpreting and using time-to-event endpoint terms, and definitions of starting and ending times, throughout the interventional oncology literature. Because of this unmet need, the SIO and the DATECAN group worked on a project with an international panel of 62 experts, and a consensus was reached on the use of the validated three-step modified Delphi consensus method.

How Can We Analyze Various Outcomes at Per-Patient, Per-Procedure, or Per-Tumor Levels and How Can We Define Them?

Outcome parameters should be analyzed appropriately at different levels, including per-patient, per-procedure, and per-tumor, when performing studies on image-guided tumor ablation, as summarized in Table 1. Of note, survival outcomes should be interpreted per-patient and not per-tumor or per-procedure. However, as an exception, local tumor progression-free survival (LTPFS) can be assessed on a per-patient or per-tumor basis. The local (tumor) progression rate can also be used, instead of LTPFS, when analyzing on a per-tumor basis as the term has been widely used in previous studies [345]. Parameters closely related to the treatment session should be analyzed per-procedure, as a synonym for the session. Such items include procedure-related side effects, direct costs, short-term complications, anesthesia technique, hospital-stay characteristics, laboratory tests, and technical success. However, technical success can also be interpreted on a per-tumor basis. The parameters related to the local efficacy that are assessed on a per-patient and per-tumor basis are as follows: LTPFS, time-to-local (tumor) progression, freedom from local or organ-specific recurrence, primary and secondary or assisted technique efficacy, residual disease, local (tumor) progression, recurrence rates, and local control. In patients with multiple index tumors (e.g., multiple colorectal metastases), standard survival estimates (Kaplan-Meier or cumulative incidence functions) may not consider the dependency of partially correlated or clustered data. Therefore, this potential limitation must be considered.
Table 1

Summary of the Use of Per-Patient, Per-Procedure, or Per-Tumor Analyses for Different Outcomes

ParameterAccepted AcronymsPer-PatientPer-ProcedurePer-Tumor
Overall survivalOSYes
Disease-specific overall survivalYes
Disease-free survivalDFSYes
Recurrence-free survivalRFSYes
Progression-free survivalPFSYes
Distant progression-free survivalDPFSYes
Procedure-related side effectsYes
Direct costsYes
Short-term complicationsYes
Anesthesia techniqueYes
Hospital-stay characteristicsYes
Laboratory testsYes
Technical successYesYes
Local tumor progression-free survivalLTPFSYesYes
Time-to-local (tumor) progressionYesYes
Freedom from local or organ-specific recurrenceYesYes
Primary technique efficacyYesYes
Secondary or assisted technique efficacyYesYes
Residual diseaseYesYes
Local (tumor) progressionYesYes
Recurrence ratesYesYes
Local controlYesYes

Adapted from Puijk et al. Radiology 2021;301:533-540 [1].

The definitions of the various oncologic endpoints are summarized in Table 2. Overall survival, defined as death from all causes, is widely used to describe survival outcomes in oncologic studies [6]. However, if the occurrence of death from causes other than the disease being studied is substantial, both overall survival and disease-specific survival should be documented. Death from causes other than the disease being explored is considered a competing risk for disease-specific survival analysis. When tumor ablation is performed for early stage disease, recurrence-free survival should be used if the intervention is likely curative (i.e., ablation of small renal tumors). When the intervention is considered potentially curative for intermediate-stage disease (i.e., ablation of colorectal liver metastases), disease-free survival should be used.
Table 2

Definitions of Various Oncologic Endpoints

ObservationDFSRFSTTRDSS*OS
Locoregional recurrenceEventEventEventIgnoredIgnored
Distant metastasesEventEventEventIgnoredIgnored
Second primary, the same cancerEventIgnoredIgnoredIgnoredIgnored
Second primary, other cancerEventIgnoredIgnoredIgnoredIgnored
Death from the same cancerEventEventEventEventEvent
Death from other cancerEventEventCensoringCensoringEvent
Non-cancer-related deathEventEventCensoringCensoringEvent
Treatment-related deathEventEventCensoringCensoringEvent
Loss to follow-upCensoringCensoringCensoringCensoringCensoring

Modified from Punt et al. J Natl Cancer Inst 2007;99:998-1003 [6]. *Synonyms for cancer-specific survival. DFS = disease-free survival, DSS = disease-specific survival, OS = overall survival, RFS = recurrence-free survival, TTR = time to recurrence

Unlike the diagnosis/prediction of static binary outcomes, the follow-up time should be considered for survival analysis and should be defined accurately [78]. The commonly used time-to-event endpoints are presented in Table 3. The definition of the starting time should differ according to the study design. For randomized controlled trials, the starting time should be the randomization date, and it is recommended that the time taken from the interventional procedure be added to the data. For single-arm prospective studies and retrospective comparative and non-comparative studies, the starting time should be the date of the first intervention.
Table 3

Definitions of Time-to-Event Endpoints Commonly Used in Image-Guided Tumor Ablation

Time-to-Event EndpointsStarting Point*Ending Point
Time to progressionStarting timeAny disease recurrence (local, regional, or distant)
Distant progression-free survivalStarting timeDistant tumor progression, but not local or regional progression
LTPFSStarting timeLocal tumor progression per tumor treated (per-tumor analysis) or per patient treated (per-patient analysis)
Time-to-local (tumor) progression, horizontally flipped LTPFSStarting timeLocal tumor progression per tumor treated
Disease-specific survivalStarting timeDeath from the same cancer
Overall survivalStarting timeDeath from all causes

*Definition of starting time differs according to the study design. LTPFS = local tumor progression-free survival

Other Terminologies Commonly Used in Image-Guided Tumor Ablation

Ablation confirmation

This refers to postprocedural imaging or any alternative technique that is implemented to allow for additional overlapping (completion) procedures, either within the same session or in a complementary completion session, in the days or weeks hereafter.

Technical success

This addresses whether the tumor was treated according to a predefined protocol and covered completely by the ablation zone using ablation confirmation techniques. Technical success rates should be documented in a research paper.

Technique efficacy

This refers to the achievement of complete tumor ablation at a prospectively defined time point, as evidenced by imaging follow-up or any alternative technique (i.e., biopsy or serologic criteria). If a patient died due to any cause before that time point, then the event should be analyzed and reported as a competing risk.

Primary efficacy rate and secondary or assisted technique efficacy rate

The former refers to the percentage of target tumors that were successfully eradicated following initial ablation. In contrast, the latter addresses the percentage of target tumors that were eventually removed with repeat ablations using ablation therapy.

Local control

This is equivalent to assisted technique efficacy, except that repeat treatments using alternative methods (other ablation therapy, radiation therapy, or surgical excision) are allowed.

Residual unablated tumor and local tumor progression

The former refers to a residual viable tumor at the ablative margin at the initial follow-up imaging. In contrast, the latter refers to the appearance of a viable tumor, provided that a residual viable tumor was not found in at least one contrast-enhanced follow-up study at the ablative margin.
  8 in total

1.  Image-guided tumor ablation: standardization of terminology and reporting criteria--a 10-year update.

Authors:  Muneeb Ahmed; Luigi Solbiati; Christopher L Brace; David J Breen; Matthew R Callstrom; J William Charboneau; Min-Hua Chen; Byung Ihn Choi; Thierry de Baère; Gerald D Dodd; Damian E Dupuy; Debra A Gervais; David Gianfelice; Alice R Gillams; Fred T Lee; Edward Leen; Riccardo Lencioni; Peter J Littrup; Tito Livraghi; David S Lu; John P McGahan; Maria Franca Meloni; Boris Nikolic; Philippe L Pereira; Ping Liang; Hyunchul Rhim; Steven C Rose; Riad Salem; Constantinos T Sofocleous; Stephen B Solomon; Michael C Soulen; Masatoshi Tanaka; Thomas J Vogl; Bradford J Wood; S Nahum Goldberg
Journal:  Radiology       Date:  2014-06-13       Impact factor: 11.105

2.  Percutaneous US/MRI Fusion-guided Radiofrequency Ablation for Recurrent Subcentimeter Hepatocellular Carcinoma: Technical Feasibility and Therapeutic Outcomes.

Authors:  Kyoung Doo Song; Min Woo Lee; Hyunchul Rhim; Tae Wook Kang; Dong Ik Cha; Dong Hyun Sinn; Hyo Keun Lim
Journal:  Radiology       Date:  2018-06-19       Impact factor: 11.105

Review 3.  Endpoints in adjuvant treatment trials: a systematic review of the literature in colon cancer and proposed definitions for future trials.

Authors:  Cornelis J A Punt; Marc Buyse; Claus-Henning Köhne; Peter Hohenberger; Roberto Labianca; Hans J Schmoll; Lars Påhlman; Alberto Sobrero; Jean-Yves Douillard
Journal:  J Natl Cancer Inst       Date:  2007-06-27       Impact factor: 13.506

4.  Comparison of no-touch multi-bipolar vs. monopolar radiofrequency ablation for small HCC.

Authors:  Arnaud Hocquelet; Christophe Aubé; Agnès Rode; Victoire Cartier; Olivier Sutter; Anne Frederique Manichon; Jérome Boursier; Gisèle N'kontchou; Philippe Merle; Jean-Frédéric Blanc; Hervé Trillaud; Olivier Seror
Journal:  J Hepatol       Date:  2016-07-13       Impact factor: 25.083

5.  Consensus Guidelines for the Definition of Time-to-Event End Points in Image-guided Tumor Ablation: Results of the SIO and DATECAN Initiative.

Authors:  Robbert S Puijk; Muneeb Ahmed; Andreas Adam; Yasuaki Arai; Ronald Arellano; Thierry de Baère; Reto Bale; Carine Bellera; Christoph A Binkert; Christopher L Brace; David J Breen; Elias Brountzos; Matthew R Callstrom; Gianpaolo Carrafiello; Julius Chapiro; Francesco de Cobelli; Veerle M H Coupé; Laura Crocetti; Alban Denys; Damian E Dupuy; Joseph P Erinjeri; Dimitris Filippiadis; Afshin Gangi; Debra A Gervais; Alice R Gillams; Tissy Greene; Boris Guiu; Thomas Helmberger; Roberto Iezzi; Tae Wook Kang; Alexis Kelekis; Hyun S Kim; Thomas Kröncke; Sharon Kwan; Min Woo Lee; Fred T Lee; Edward W Lee; Ping Liang; Birgit I Lissenberg-Witte; David S Lu; David C Madoff; Giovanni Mauri; Maria Franca Meloni; Robert Morgan; Gregory Nadolski; Govindarajan Narayanan; Isabel Newton; Boris Nikolic; Franco Orsi; Philippe L Pereira; Uei Pua; Hyunchul Rhim; Jens Ricke; William Rilling; Riad Salem; Hester J Scheffer; Constantinos T Sofocleous; Luigi A Solbiati; Stephen B Solomon; Michael C Soulen; Daniel Sze; Raman Uberoi; Thomas J Vogl; David S Wang; Bradford J Wood; S Nahum Goldberg; Martijn R Meijerink
Journal:  Radiology       Date:  2021-09-28       Impact factor: 11.105

6.  Radiofrequency Ablation Using a Separable Clustered Electrode for the Treatment of Hepatocellular Carcinomas: A Randomized Controlled Trial of a Dual-Switching Monopolar Mode Versus a Single-Switching Monopolar Mode.

Authors:  Jae Won Choi; Jeong Min Lee; Dong Ho Lee; Jung Hwan Yoon; Yoon Jun Kim; Jeong Hoon Lee; Su Jong Yu; Eun Ju Cho
Journal:  Korean J Radiol       Date:  2020-07-22       Impact factor: 3.500

Review 7.  Review of Statistical Methods for Evaluating the Performance of Survival or Other Time-to-Event Prediction Models (from Conventional to Deep Learning Approaches).

Authors:  Seo Young Park; Ji Eun Park; Hyungjin Kim; Seong Ho Park
Journal:  Korean J Radiol       Date:  2021-07-01       Impact factor: 3.500

  8 in total

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