Analyse-it Method Validation Edition

Analyse-it Method Validation Edition

 

 

 

Validate and verify your analytical and diagnostic methods to meet the demands of regulatory compliance.

 

 

The leading software package for method validation for over 20-years.

 

Analyse-it is developed for and is in use at thousands of ISO/IEC 17025 accredited testing and calibration laboratories, ISO 15189 accredited medical laboratories, CLIA '88 regulated medical laboratories, and IVD manufacturers for development, support, product labeling and FDA 510(k) submissions.

 

“Analyse-it has been a tremendous help. I've published and presented at national cardiology meetings and couldn't have accomplished most of my research without it. Using Analyse-it, I even found errors or omissions in the work of our statistician!”

Regina S. Druz, MD, FACC, FASNC

Director, Nuclear Cardiology

North Shore University Hospital

“We use Analyse-it frequently for our verification and pre-verification work, in accordance with CLSI guidelines for in-vitro diagnostics. It's saved time and effort compared to the hodge-podge of applications we used before, JMP, SAS, etc...”

Brian Noland, Ph.D.

Principle Scientist, Product Development

Biosite / Inverness Medical Innovations

 

“We use Analyse-it for the analysis of data necessary to file 510k. We chose Analyse-it because it works in Excel, includes CLSI protocols, and, unlike EP-Evaluator, lets us analyze data directly from equipment without typing.”

Thomas D Harrigan, Ph.D.

Technical Product Manager

Alfa Wassermann Diagnostic Technologies

 

“I used Analyse-It for many product development, product troubleshooting, and technology evaluation activities... your product was the easiest to use, was accurate, and produced publication ready reports.”

Stanley F. Cernosek, Ph.D.

Clinical Chemistry Reagent Development

Beckman Coulter, Inc.

 

Built for CLSI protocols

 

The latest Clinical and Laboratory Standards Institute (CLSI) method validation protocols are recognized by the College of American Pathologists (CAP), The Joint Commission, and the US Food and Drug Administration (FDA).

 

That's why we included extensive support for 11 CLSI protocols

 

Validate and verify measurement system performance characteristics

 

It’s essential to ensure the performance characteristics (precision, trueness, linearity, interferences, detection capability) of a measurement procedure meet the requirements for intended use. Manufacturers (IVD companies) must establish performance during product development to feedback into the development process, for FDA 510k submissions and product marketing, and to support customers in the field. Laboratories must verify they can achieve the manufacturer's claimed performance during implementation of a new measurement system, during regulatory inspections (under the CLIA ’88 act), and as part of proficiency testing (PT) schemes. Measurement systems analysis (MSA) lets you determine all these important performance characteristics in one analysis.

 

 

 

Examine diagnostic test performance to find the most effective

 

Rated best ROC curve software in Clinical Chemistry March 2003 vol. 49 no. 3 pg. 433-439, Analyse-it lets you establish and compare the ability of a diagnostic test to correctly diagnose patients. Explore how the test differentiates between positive and negative cases and explore optimum decision thresholds factoring in the costs of misdiagnosis.

 

 

Compare methods and evaluate the impact of making changes

 

When introducing a new measurement procedure you want to see how it stacks-up against your existing procedure or evaluate its performance against the gold-standard. Bland-Altman lets you see the agreement between methods and what effect the differences between methods might have on clinical interpretation. More advanced procedures like Deming regression and Passing-Bablok tell you the bias between methods, how medical decision points may be affected, and let you test if bias meets performance requirements.

Establish reference intervals to make clinical diagnoses

 

Reference intervals are essential for clinicians to interpret results and make a diagnosis. As a laboratory it's your job to provide normal reference ranges they can rely on. With the widest range of methods available in any software package, the ability to partition the intervals by factors such as sex, age, ethnicity, Analyse-it makes it easy to establish reference ranges or transfer them to a new measurement procedure.

 

 

 

 

Technical specification

 

System requirements

• Microsoft Excel 2007, 2010, 2013, 2016, 2019 and Office 365 (32- and 64-bit)
• Microsoft Windows Vista, 7, 8, 10, Server 2003, 2008, 2012, & 2016
• 2GB RAM minimum recommended
• 80MB disk space

 

Method comparison

 

Quantitative methods

• Supports singlicate, duplicate, and replicate measurements
• Compare commutability of samples with prediction intervals new in v4.90
• Reduce measuring interval to linear range, or partition into multiple intervals with different relationships (e.g. constant / relative differences) new in v4.00
• Ordinary and Weighted linear regression average bias with confidence intervals
• Deming and Weighted Deming regression average bias with Jacknife confidence intervals
• Passing Bablok regression average bias with Passing-Bablok or Bootstrap confidence
• Predict bias with confidence intervals at important decision levels
• Test equality (no difference) or equivalence (difference within an allowable difference) at decision levels
• Scatter plot, with average bias, average bias confidence bands, identity line, and allowable difference band
• Vary color of points by a factor
• Difference/relative difference/ratio plot against X or mean of methods with allowable difference band and histogram of differences
• Bland-Altman limits of agreement with mean, median, and linear fit bias new in v3.75
• Mountain plot with allowable difference band new in v3.71
• Residual plot, raw and standardized, with histogram of residuals
• CUSUM linearity plot and Kolmogorov-Smirnov linearity test
• Precision (SD or CV) and precision plots for each method
• Pearson r correlation coefficient
• Supports CLSI EP09-A3 Measurement Procedure Comparison and Bias Estimation Using Patient Samples and CLSI EP21 Estimation of Total Analytical Error for Clinical Laboratory Methods

 

Qualitative methods

• Proportion in positive agreement / negative agreement with Clopper-Pearson exact or Wilson score confidence intervals
• Kappa and Weighted Kappa for chance-corrected agreement with Wald Z confidence interval
• Kappa test for agreement

 

Measurement Systems Analysis (MSA)

 

• Unified analysis to examine performance characteristics of a method (bias, precision, linearity, interferences, and detection limits)
• Flexible balanced and unbalanced experiment design: up to 3 random nested factors new in 4.60 (e.g. day, run, laboratory), and 1 fixed factor (e.g. level)
• Variance function fit: 4 parameter function with turning point new in v4.91
• Generalized ESD outlier identification (Grubb’s test for more than one outlier) new in v4.95
• Scatter plot and difference plots
• Variability of measurements plot

 

Bias / Trueness (new in v4.00)

• Bias with confidence interval
• Difference plot of bias against assigned values with allowable bias bands
• Test equality (no bias) or equivalence (bias within allowable bias)
• Supports CLSI EP15-A3 User Verification of Precision and Estimation of Bias and EP10-A3-AMD Preliminary Evaluation of Quantitative Clinical Laboratory Measurement Procedures

 

Linearity

• Fit models: linear, polynomial (up to 5th order), forward stepwise polynomial, and best (2nd or 3rd) polynomial regression
• Weighted models for non-constant SD across the measuring interval new in v5.00
• Adjust measuring interval to find linear range new in v5.00
• Difference between linear and nonlinear fit with Hsieh-Liu confidence intervals
• Test equality (no difference) or equivalence (difference within allowable nonlinearity)
• Difference plot of difference against assigned values with allowable nonlinearity band
• Supports Emancipator-Kroll linearity and CLSI EP06-A Evaluation of the Linearity of Quantitative Measurement Procedures and EP10-A3-AMD Preliminary Evaluation of Quantitative Clinical Laboratory Measurement Procedures

 

Precision

• Precision as variance, SD, or CV% with Exact, Satterthwaite, and MLS confidence
• Abbreviated reproducibility/repeatability, and detailed intermediate precision components
• ANOVA table
• Terminology depending on conditions of measurement: total / within, reproducibility / repeatability, or laboratory / repeatability
• X2 test against precision claim
• Precision profile of SD or CV
• Variance function fit: constant variance, constant CV, mixed constant / proportional variance, and Sadler 3 parameter power, and 3 parameter alternative power functions new in v4.00
• Supports CLSI EP05-A3 Evaluation of Precision of Quantitative Measurement Procedures , EP10-A3-AMD Preliminary Evaluation of Quantitative Clinical Laboratory Measurement Procedures and EP15-A3 User Verification of Precision and Estimation of Bias

 

Detection limits (new in v4.00)

• Limit of blank (LoB): of a blank material (parametric SD or non-parametric quantile), or using precision profile variance function
• Limit of detection (LoD): pooled SD of non-blank materials, or using precision profile variance function
• Limit of detection (LoD) using Probit regression new in v5.50
• Limit of quantitation (LoQ) using precision profile variance function
• Frequency density histogram of detection capability, LoB, and LoD
• Supports CLSI EP17-A2 Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures

 

Reference interval

 

• Partition by factor(s) for separate analysis of groups (new in 4.0)
• Frequency distribution histogram with normal overlay and reference limits
• Tukey outlier box plot
• Transform reference values with reciprocal, log, square and cube root, Box-Cox new in 3.52, and Manly exponential & 2-stage exponential / modulus new in 4.0 functions
• Shapiro-Wilk or Anderson-Darling normality test of reference distribution
• Normal quantile plot
• Supports CLSI EP28-A3C (Formerly C28-A3C) Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory

 

Establish reference limits

• Normal quantile
• Nonparametric quantile, Harrell-Davis quantile, and Bootstrap quantile
• Robust bi-weight quantile for symmetric and skewed small samples
• Various quantile computation methods (N+1)p, Np+1/2, and (N+1/3)p+1/3

 

Transfer / verify limits

• Transfer existing reference interval using method comparison regression function
• Binomial test for proportion inside reference interval

 

Diagnostic performance

 

ROC

• Diagnostic performance for 1 test, up to 10 paired tests, or up to 10 independent tests/groups
• Number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN)
• Sensitivity/Specificity
• Likelihood ratios
• Predictive values
• Odds ratio, and Youden's index
• Bi-histogram and dot-plot of positive/negative outcomes new in v4.0
• ROC curve plot: Sensitivity (TPF) vs 1-Specificity (FPF) with no discrimination line
• Wilcoxon-Mann-Whitney area under curve with DeLong-DeLong-Clarke-Pearson confidence interval
• Z test of area under curve is better than chance decision
• Compare DeLong-DeLong-Clarke-Pearson difference in area under curves and test for equality (no difference), equivalence (difference negligible), or non-inferiority (not unacceptably worse than a standard test)
• Decision plot of accuracy over all possible decision thresholds: Sensitivity vs Specificity, Likelihood ratios, Predictive values, or Cost
• Find optimal decision threshold based on cost of diagnosis/misdiagnosis
• Predict false positive fraction (FPF) at: Fixed sensitivity, Sensitivity at fixed FPF, or Sensitivity/FPF at fixed threshold.
• Supports CLSI EP24-A2 (Replaces GP10-A) Assessment of the Diagnostic Accuracy of Laboratory Tests Using Receiver Operating Characteristic Curves

 

Qualitative

• Diagnostic performance for 1 test, 2 paired tests, or 2 independent tests/groups
• Sensitivity/Specificity with Clopper-Pearson exact or Wilson score confidence interval
• Likelihood ratios with Miettinen-Nurminen score confidence interval
• Predictive values with Mercado-Wald logit confidence interval
• Odds ratio, and Youden's index
• Mosaic plot of outcomes
• Difference between sensitivity/specificity with Newcombe or Tango score confidence intervals
• McNemar-Mosteller exact, Fisher exact, and Score Z test for equality of sensitivity/specificity
• Supports CLSI EP12-A2 User Protocol for Evaluation of Qualitative Test Performance