Interobserver and Intraobserver Variability in Measurement of Non–Small-Cell Carcinoma Lung Lesions: Implications for Assessment of Tumor Response

Erasmus, Jeremy J.; Gladish, Gregory W.; Broemeling, Lyle D.; Sabloff, Bradley S.; Truong, Mylene T.; Herbst, Roy S.; Munden, Reginald F.

doi:10.1200/jco.2003.01.144

Cited by 427 publications

(286 citation statements)

References 23 publications

Supporting

Mentioning

261

Contrasting

Unclassified

Order By: Relevance

“…Using the target lesions shown in Table 1, this change represents a decrease from 3 to 2.1 cm, or increase from 3 to 3.6 cm in the greatest diameter. Lesions of this size are subject to greater measurement error and subsequent misclassification than larger tumors even when they are read by a single radiologist (20). In addition, lymph nodes do not disappear even if the tumor is eradicated and a response may represent a shrinkage of minimally enlarged node to normal size, e.g., 2.2 to 1.8 cm (21).…”

Section: Eligibility Criteriamentioning

confidence: 99%

Prostate Cancer Clinical Trial End Points: “RECIST”ing a Step Backwards

Scher

Morris

Kelly

et al. 2005

Clinical Cancer Research

122

View full text Add to dashboard Cite

Purpose:To relate clinical issues to the clinical manifestations of prostate cancers across disease states using the eligibility and outcome criteria defined by Response Evaluation Criteria in Solid Tumors (RECIST). Experimental Design: The manifestations of prostate cancer that characterize localized, recurrent, and metastatic disease were considered using the eligibility criteria for trials defined by RECIST. To do so, we analyzed the sites, size, and distribution of lesions in patients enrolled on contemporary Institutional Review Board^approved trials for progressive castrate and noncastrate metastatic disease. Prostate-specific antigen (PSA) levels were also assessed. RECISTdefined outcome measures for tumor regression were then applied to the metastatic patient cohorts, and separately to the states of a rising PSA (noncastrate and castrate) and localized disease. Results: Only 43.5% of men with castrate metastatic and 16% of noncastrate metastatic disease had measurable target lesions >2 cm in size. Overall, 84.4% of the target lesions were lymph nodes, of which 67.7% were z2 cm in the long axis.There are no target lesions in patients in the states of a rising PSA and localized disease, making them ineligible for trials under these criteria. PSAbased eligibility and outcomes under RECIST conflict with established reporting standards for the states of a rising PSA and castrate metastatic disease. The clinical manifestations of prostate cancer across multiple disease states are not addressed adequately using the eligibility criteria and outcomes measures defined by RECIST. Important treatment effects are not described. Conclusions: Trial eligibility and end points based solely on tumor regression are not applicable to the majority of the clinical manifestations of prostate cancers representing all clinical states. Treatment effects can be described more precisely if eligibility criteria are adapted to the clinical question being addressed and clinical state under study, focusing on the duration of benefit defined biochemically, radiographically, and/or clinically.

show abstract

Section: Eligibility Criteriamentioning

confidence: 99%

Prostate Cancer Clinical Trial End Points: “RECIST”ing a Step Backwards

Scher

Morris

Kelly

et al. 2005

Clinical Cancer Research

122

View full text Add to dashboard Cite

show abstract

“…4. The mean relative error never exceeded more than 10%, which is the upper bound for the measurement error of tumor assessments (11,12). With 100% dropout, some of the simulation replications exceeded 10% error, but only at later time points of a year of more.…”

Section: Methodsmentioning

confidence: 99%

Effect of Censoring Due to Progressive Disease on Tumor Size Kinetic Parameter Estimates

Bonate

Suttle

2013

AAPS J

View full text Add to dashboard Cite

Abstract. Tumor growth profiles were simulated for 2 years using the Wang and Claret models under a phase 3 clinical trial design. Profiles were censored when tumor size increased >20% from nadir similar to clinical practice. The percent of patients censored varied from 0% (perfect case) to 100% (real-life case). The model used to generate the data was then fit to the censored data using FOCE in NONMEM. The percent bias in the estimated model parameters determined with censored data was compared to the true values. A total of 100 simulation replicates was used. For the Wang model, under clinical conditions (100% censoring), the parameter related to tumor reduction SR was underpredicted by 30% and the parameter related to tumor growth PR was underpredicted by ∼45%. Most of the variance components in the model were within ±20% of the true values. However, biased parameter estimates in the Wang model did not translate to biased tumor size predictions as the mean percent prediction error between true and model predicted tumor size never exceeded 10%. For the Claret model, at 100% censoring, the tumor growth parameter KL was unaffected by censoring. Both tumor shrinkage parameters, KD and λ, were overestimated by ∼20% in both cases. Future research needs to be directed to develop less empirically based models and to use simulation as a way to improve clinical oncology trials designs.

show abstract

“…The lung tumor size measurements data from [19] which motivated this work and are analyzed later in this article, provide a specific example of this phenomenon. The information was gathered from August 2000 to May 2001.…”

Section: Journal Of Medical Statistics and Informaticsmentioning

confidence: 99%

Assessing inter-rater agreement between multiple medical instruments with heteroscedastic measurements

Dassanayake¹,

Nawarathna²

2017

J Med Stat Inform

View full text Add to dashboard Cite

Background: In clinical medicine, agreement evaluation plays a major role in determining the compatibility and the accuracy of newly introduced methods with pre-existing methods. These methods may be assays, clinical observers, medical devices etc. It is vital to assess the compatibility and the accuracy of these newly introduced techniques because they deal with the measurements of the human body, such as blood pressure, cholesterol level, heart rate etc. In practice, agreement evaluation is carried out among two methods of measurements and deals with the data that are homoscedastic. The main objective of this study is to extend the standard mixed model to allow the error variances to depend on magnitude of measurement and evaluate agreement between multiple methods assuming the new model, taking the heteroscedasticity into account. Methods: In order to assess the agreement, there are two typical steps in method comparison studies. The first step is to model the data using the Heteroscedastic mixed effects model. The model fitting is carried out by using two main approaches, namely the mean method and the best linear unbiased predictor method. After fitting the model for the second step, the agreement evaluation is carried out using Concordance correlation coefficient and Total deviation index. Results: The illustrative example contained five methods of measurements and was with heteroscedastic measurements. First, the model fitting was carried out according to the two approaches and the resulting parameters were almost identical. After the model fitting, the agreement evaluation was performed. According to the values resulted from the agreement measurements, it is clear that all five methods agree sufficiently well with the reference method. Conclusions: The proposed model can be used to model the method comparison data with heteroscedastic measurements with multiple methods of measurements as well as balanced and unbalanced data designs. Under the proposed model, the agreement evaluation methodology for comparing multiple methods is also developed taking heteroscedasticity into account.

show abstract

Interobserver and Intraobserver Variability in Measurement of Non–Small-Cell Carcinoma Lung Lesions: Implications for Assessment of Tumor Response

Abstract: Measurements of lung tumor size on CT scans are often inconsistent and can lead to an incorrect interpretation of tumor response. Consistency can be improved if the same reader performs serial measurements for any one patient.

Cited by 427 publications

References 23 publications

Prostate Cancer Clinical Trial End Points: “RECIST”ing a Step Backwards

Prostate Cancer Clinical Trial End Points: “RECIST”ing a Step Backwards

Effect of Censoring Due to Progressive Disease on Tumor Size Kinetic Parameter Estimates

Assessing inter-rater agreement between multiple medical instruments with heteroscedastic measurements

Contact Info

Product

Resources

About