Contraceptive Efficacy Estimate

Enter study data or clinical experience to compute the Pearl Index — pregnancies per 100 woman-years — for a contraceptive method.

Exposure time

225.00 woman-years

Pearl Index

0.89

Pregnancies per 100 woman-months

0.07

Very high efficacy: Pearl index <1 indicates extremely effective contraception (e.g., sterilization, IUD, implants).

How to Use This Calculator

1

Collect contraceptive cohort data

Record the number of participants, total observation period, and unintended pregnancies.

2

Enter total exposure months

Multiply participant count by months of participation after excluding drop-outs or non-use intervals.

3

Interpret the Pearl Index

Compare results across contraceptive methods and with perfect-use versus typical-use benchmarks.

Formula

Woman-years = (Number of women × Exposure months) ÷ 12

Pearl Index = (Pregnancies ÷ Woman-years) × 100

Pregnancies per 100 woman-months = (Pregnancies ÷ (Women × Months)) × 100

Full Description

The Pearl Index quantifies contraceptive effectiveness by standardizing pregnancy incidence to 100 woman-years of exposure. It is widely used in clinical trials and comparative studies but can be influenced by sample size, adherence, and differences in exposure time. Perfect-use rates measure efficacy under ideal conditions, while typical-use rates reflect real-world adherence and user error. Interpret Pearl Index alongside continuation rates and user satisfaction for a comprehensive assessment.

Frequently Asked Questions

How does Pearl Index compare to life-table analysis?

Life-table (Kaplan–Meier) analysis accounts for time to pregnancy and drop-outs, offering more precision for long-term studies.

Can Pearl Index be used for small cohorts?

It can, but small sample sizes exaggerate fluctuations. Report confidence intervals when possible.

What is the difference between typical and perfect use?

Perfect use reflects consistent, correct use every time. Typical use includes human error, missed doses, or improper application.

Why adjust for woman-years?

Standardizing to woman-years enables comparison across studies with differing durations and cohort sizes.