Clinical Chemistry I - Method Selection Quiz

Clinical Chemistry I - 0202304

• Course instructor: Mohammad Qabajah
• Email: [email protected]

Week 03&04 - Method Selection and Evaluation

• Objectives:
  • Familiarize with three major areas for analytical method selection
  • Understand analytical performance of methods
  • Know analytical and practical criteria, especially for automated methods
  • Review statistical concepts related to analytical method performance
  • Compare analytical performance criteria using Bland-Altman method and correlation regression

Method Selection: Considerations

• Three major considerations:
  • Medical Usefulness (Patient needs)
  • Analytical Performance (Calibration, Precision, Accuracy)
  • Practical Criteria (Protocol, Conditions)

Method Selection: Medical Usefulness

• Achieving optimal patient care
• Determining clinical needs for lab tests

Method Selection: Analytical Performance

• Calibration (Correlation between instrument signal and analyte concentration)
• Precision (closeness between independent results)
• Accuracy (closeness of agreement of a single measurement with True Value).
• Analytical Range (concentration range for reliable measurements)
• Detection Limit (lowest analyte concentration detectable)
• Clinical Sensitivity and Specificity

Method Selection: Practical Criteria

• Detailed protocol
• Reference materials
• Reagent composition and stability
• Technologist skills
• Potential hazards and waste
• Specimen requirements
• Equipment requirements
• Cost-effectiveness
• Computer platforms and interfacing
• Availability of technical support
• For automated procedures:
  • Pipetting precision
  • Carryover specimen & reagent
  • Detector imprecision
  • Time to report
  • On-board reagent stability
  • Overall throughput
  • Mean time to instrument failure
  • Mean time to repair

Statistical Terms

• Mean: Sum of all values divided by the total number of values
• Standard deviation: Measure of the amount of variation or dispersion of a set of values
• Coefficient of Variation (CV): Ratio of standard deviation to the mean, expressed as a percentage

Gaussian Probability Distribution

• Describes the distribution of many biological variables
• Symmetrical bell-shaped curve with central tendency (mean).
• 68% of values fall within one standard deviation of the mean
• 95% of values fall within two standard deviations of the mean
• 99.7% of values fall within three standard deviations of the mean

Analytical Methods: Basic Terms

• Calibration (معايرة)
• Linearity
• Trueness/Accuracy
• Precision
• Limit of Detection

Calibration

• Correlation between instrument signal and analyte concentration
• Linearity: Relationship between measured and expected values over the range of analytical measurements

Calibrator

• Known quantity
• Linear (immunoassays) and curved calibration curves
• Must be monotonic (always increasing or decreasing) for accurate calibration

Calibration (additional notes)

• Random dispersion of instrument signal at a given concentration transforms into dispersion on the measurement scale
• Modern automated machines have very small variations, making calibrations stable

Trueness and Accuracy

• Trueness: Closeness of agreement of the average measured value to the true value
• Accuracy: Closeness of agreement of a single measurement to the true value

Trueness and Accuracy – Related Terms

• Recovery: Difference between measured concentration and the amount added.
• Drift: Differences caused by instrument or reagent instability over time.
• Carryover: Differences caused by fraction of previously measured samples affecting the next sample's measurement.
• Bias: Mathematical difference between the average measurement and true value

Precision

• The closeness between independent results of measurements obtained under stipulated conditions
• Imprecision: Measured by SD or CV; inversely related to precision; caused by random error
• Types of measurement
  • Between run precision
  • Interlaboratory precision

Precision – Related Terms

• Repeatability: Closeness between results of successive measurements under the same conditions
• Reproducibility: Closeness between results of successive measurements under changed conditions

Analytical Measurement Range and Limits of Quantification

• Measuring interval reportable range
• Analyte concentration range where measurements are within declared tolerances for imprecision and bias of the method

Analytical Range

• Calibration curve for defining LLOQ (Lower Limit of Quantification) and ULOQ (Upper Limit of Quantification)
• Measured intensity, dynamic range, not detectable, dynamic range is the region of analyte concentrations where there is a linear relationship between measured signal and analyte concentration
• Not quantifiable - concentrations are outside the range of reliable measurement.

Limit of Detection (LOD) & Limit of Blank (LOB)

• Important for many analytes, especially hormones
• Factors affecting: Instrument sensitivity, background noise, sample matrix, analyte properties
• Errors: Type I (no analyte, signal present); Type II (analyte present, no signal)
• Reporting: not detectable <LOD or zero, LOB; detectable >zero, detected.

Analytical Sensitivity

• The ability to assess small variations in analyte concentration
• Depends on: Calibration curve slope (direct relationship) and random variation (inverse relationship)

Analytical Specificity and Interference

• The procedure's ability to determine the target analyte concentration in the presence of interfering substances.

Analytical Goals

• Based on clinical outcomes and biological variation
• Imprecision (σ²within-B + σ²between-B)
• Limits set by regulatory bodies

Method Comparison

• Comparison study
  • Number of samples needed
  • Distribution of analyte concentrations
  • Representativeness of samples
  • Practical aspects (storage, sample treatment, anticoagulants, measurement times)
  • Ethical issues

Comparison of Methods - Difference Bland-Altman Plot

Comparison of Methods - Regression Analysis

• Estimate relationships between dependent and 1+ independent variables.
• Ordinary Least-Squares Model (OLS)
• Beware of outliers

Comparison of Methods - Proportional Random Error

• Depends on the change in a specific variable
• Measurable amount, X divided by y, will equal the same constant.

Comparison of Methods – Traceability

• Unbroken chain of comparisons of measurements leading to a known reference value
• Property of the result of a measurement or the value of a standard

Comparison of Methods – Uncertainty

• Parameter associated with measurement result indicating dispersion of values, expressed by standard deviation
• Affected by preanalytical variation, method imprecision, sample-related random interference, uncertainty, bias corrections (traceability) and associated (calibration).

Week 05&06 - Clinical Evaluation of Laboratory Tests

• Objectives:
  • State the formulas for clinical sensitivity, specificity and predictive values.
  • State how predictive value is affected by prevalence.
  • Construct a receiver operating characteristic plot (ROC) from diagnostic tests.
  • Interpret difference plot from method comparison.

Agreement of test results: Accurate diagnosis

• Sensitivity and Specificity
• Predictive Values
• Prevalence
• Likelihood Ratio (LR)
• Odds Ratio (OR)

Review: Gaussian Probability Distribution

• Normal distribution is symmetric and bell-shaped
• 68% of the values fall within 1 SD
• 95% of the values fall within 2 SD
• 99.7% of the values fall within 3 SD

Sensitivity and Specificity

• Sensitivity: True Positive Rate (Proportion of subjects with disease who have a positive result)
• Specificity: True Negative Rate (Proportion of subjects without disease who have a negative result)

Negative and Positive

• Disease absent, true negatives
• Disease absent, false negatives
• Disease present, false positives
• Disease present, true positives

Reference Method (Gold/Reference Standard)

• Best current practice for establishing presence of a disorder
• Screening: High sensitivity (low FN) to catch most cases, but may have many false positives
• Diagnostic: High specificity (low FP) to avoid misdiagnosis, but may miss some cases.
• Screening vs Diagnostic tests require confirmatory tests

Sensitivity and Specificity (Table)

• Table showing TP, FP, TN, FN for calculating sensitivity and specificity.

Sensitivity and Specificity (Formulas)

• Sensitivity formula: TP / (TP + FN)
• Specificity formula: TN / (TN + FP)

Predictive Values

• Positive Predictive Value (PV+): TP / (TP + FP)
• Negative Predictive Value (PV-): TN / (TN + FN)
• Predictive Values(PV+) and (PV-) depend on prevalence

Prevalence

• The frequency of disease in a population

Example: Sensitivity, Specificity, PV+, and PV-

• Example demonstrating calculations to find Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value.

Likelihood Ratio (LR)

• Likelihood a given test result is expected in a patient with the target disorder versus a patient without it.
• +LR: Sensitivity/(1-Specificity)
• -LR: (1-Sensitivity)/Specificity
• LR > 10 is good, LR < 0.1 is good for negative test.

Likelihood Ratio Example

• Example demonstrating application of likelihood ratios to determine probability of a result being positive or negative.

Likelihood Ratio Nomogram

• Helps estimate pretest probability and post-test probability.

Test your understanding of analytical method selection and evaluation in Clinical Chemistry. This quiz covers key concepts such as medical usefulness, analytical performance, and statistical methods relevant to laboratory practices. Prepare to evaluate different criteria that influence patient care and lab tests.