Related Experiment Video
Updated: Jun 29, 2026
12:40
A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors
Published on: December 7, 2014
15.0K
Validation of a Lenvatinib Assay: A Pilot Study.
Monica Majumder1, Lucy E Ding1,2, Cameron Wood2
1Department of Endocrinology and Diabetes, Royal North Shore Hospital, Sydney, NSW, Australia.
Endocrine Research
|May 22, 2025
Summary
A new mass spectrometry assay accurately measures lenvatinib levels in thyroid cancer patients. This development is crucial for optimizing treatment and managing adverse events, despite observed variability in drug levels.
Area of Science:
- Oncology
- Pharmacology
- Analytical Chemistry
Background:
- Lenvatinib improves survival in radioiodine-refractory thyroid cancer.
- Treatment-related adverse events (TRAEs) often lead to dose adjustments.
- Accurate monitoring of lenvatinib levels is needed due to lack of validated clinical assays.
Purpose of the Study:
- To develop and validate a mass spectrometry assay for quantifying plasma lenvatinib.
- To assess peak and trough lenvatinib levels in patients with thyroid cancer.
Main Methods:
- A pilot prospective single-center study was conducted.
- High-performance liquid chromatography tandem mass spectrometry (LC-MS/MS) was used for assay development.
- Plasma lenvatinib levels, dosage, TRAEs, and disease progression were recorded.
Main Results:
- A novel LC-MS/MS assay for lenvatinib quantification was successfully developed.
- Trough levels ranged from 4.60 to 30.53 µg/L (median 21.74 µg/L).
- Peak levels varied significantly, with medians of 129.56 µg/L (10mg dose) and 185.23 µg/L (14mg dose).
Conclusions:
- The developed LC-MS/MS assay enables accurate quantification of plasma lenvatinib.
- Significant variability in lenvatinib levels was observed despite consistent dosing.
- Further research is needed to determine the clinical utility of lenvatinib drug monitoring in thyroid cancer.
Related Concept Videos
02:07Blind Procedures
Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which child was...
01:37Statistical Significance
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
01:24Testing a Claim about Population Proportion
A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
01:11Testing a Claim about Mean: Known Population SD
A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
01:17Wald-Wolfowitz Runs Test I
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
The test works...
01:17Wald-Wolfowitz Runs Test II
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...