Positive Predictive Value (PPV1, PPV2, PPV3) Calculator
PPV1, PPV2, and PPV3 ask one question about patients with a positive breast imaging finding: how many had a malignant biopsy outcome within the year that followed? So what separates the three? Only where the patient was in the breast care pathway when we stopped to ask. Was it after a positive finding on the screening mammogram (PPV1), when a biopsy was recommended (PPV2), or when the biopsy was actually completed and the results returned (PPV3)?
Published August 10, 2026 / Version MammoToolbox.PPV.2.1
Standard ACR BI-RADS Atlas, 5th edition, with a BI-RADS v2025 scope note in Sources
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What this tool does
One question. Three places on the pathway where we stop and ask it.
The mammography medical outcome audit (MMOA) reports positive predictive value at three points along the diagnostic pathway1014. The question never changes. Of the patients carrying a positive finding at this moment, how many ended the year with a malignant biopsy outcome? What changes is the moment we choose to stop and count.
Patients leave the pathway between those moments, and they leave for reasons that have nothing to do with how the images were read. A workup resolves as benign. A biopsy is recommended and never scheduled. A biopsy happens and the pathology never comes back. Each departure changes who is left to count, so the percentage usually climbs from PPV1 to PPV3. That climb is mostly attrition rather than improvement.
Which raises the question this calculator exists to answer: if the number moves for reasons that have nothing to do with interpretive skill, what is your audit actually measuring?
Important: This calculator is for informational and educational purposes only. It does not provide medical, legal, regulatory, financial, or other professional advice. Results are estimates only and may be inaccurate or unsuitable for your circumstances. Consult a qualified professional before acting on any output. Use is at your own risk.
Interactive
Build your audit cohort
The figures loaded below are worked examples, not real audit data. They model a practice reading roughly 7,200 screening mammograms a year, and they exist to show how the inputs push against one another. Every value is limited by the one above it, because each group is a subset of the group before it. In outcome terms that means FP1 is at least FP2, and FP2 is at least FP3 plus the undefined cases. Replace any number with your own counts at any time, and results update instantly.
There are two ways in. TP and FP entry is the default. It is the shape your audit already reports, and it builds each denominator the way the formula does1, by adding true positives to false positives. Switch to cohort counts if you would rather reason down the pathway from total screening volume. Both routes drive the same calculation and stay in sync, so you can enter one way and read the other.
Input parameters
Sample data, not your data
Each scenario above is a worked example built on the same 7,200 exam year, so the four can be compared directly. Each one isolates a different way the numbers break. Pick one, then drag a single slider and watch which measures move and which stay still.
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One true positive count, three false positive counts. That is the Atlas construction, not a simplification made here. TP carries no subscript in any of the three formulas, and FP carries one in all three1.
All screening examinations interpreted in the audit period.
Tissue diagnosis of cancer within one year of a positive examination1. One count, applied at all three stopping points.
A positive screening finding that resolved as negative. The recall was completed, the workup was done, and no cancer was diagnosed within one year1. Assembling this count means knowing the outcome of every positive screening finding, including the BI-RADS 3 that returns at four to six months.
Denominators built from your counts
All screening examinations interpreted during the audit period. Diagnostic examinations are excluded.
BI-RADS 0, 3, 4, and 5 at screening1. Every one of these is a recall. Category 0 returns for additional imaging, category 3 returns at a four to six month interval, and categories 4 and 5 return immediately for an interventional procedure.
Adjusted down. The recall cohort cannot exceed total screening volume.
Cases assessed BI-RADS 4 or 5 and referred for tissue sampling1, counted after the diagnostic workup resolves the recall.
Adjusted down. Biopsy recommendations cannot exceed the recall cohort.
Every tissue sampling procedure completed, whether or not a result came back. The gap between this number and the one above is your compliance loss. How many of these produced a usable outcome is the next slider.
Adjusted down. Completed biopsies cannot exceed biopsy recommendations.
Tissue-confirmed malignancies arising from this screening cohort, confirmed within twelve months1. This single count is the numerator for all three positive predictive values.
Adjusted down. Confirmed cancers cannot exceed completed biopsies.
Results
The ACR BI-RADS Atlas publishes no PPV3 range in its screening table. It publishes 20% to 45% in its diagnostic table, for workup of abnormal screening1, which is the pathway this calculator models, so that is the range applied here. As a second view, the 25th to 75th percentile of screening radiologists in the ACR National Mammography Database is 20.0% to 35.6%5.
The three stopping points, drawn to scale
Each bar is the same pathway, counted at a later moment. The teal block is the malignant outcomes. Watch the bar around it collapse as patients leave the pathway, while the percentage climbs on its own. In a fully reconciled audit the teal block shrinks a little at each stop too, because some cancers are confirmed after the patient has already left4.
Read the top bar first. It shows the screened population and the share of it that carried a positive finding, which is your abnormal interpretation rate. The three bars below are that slice magnified to full width, because at true scale they would be too small to compare. The trapezoid marks where the magnification happens.
Audit context
Why PPV1 is quietly the most important of the three
Cancer detection rate is not an independent measure. It is the product of how often you recall and how well you recall. Two practices can post the same detection rate with wildly different recall behavior, and only PPV1 tells them apart. One caution on the identity: it recovers screen-detected cancers only, so interval cancers diagnosed after a negative screening examination are not represented in either side of that equation.
This relationship is not an assumption of this tool. Blanks, Moss, and Wallis established it in the Journal of Medical Screening in 20012. They introduced the PPV-referral diagram, in which cancer detection rate appears as isobars across a plot of positive predictive value against referral rate. A BCSC expert panel later dropped PPV1 as a separate criterion for the same reason. PPV1 must reach 3% for a radiologist to hold cancer detection rate and recall rate inside the ranges under review3. That panel also built its CDR, recall, and PPV1 criteria specifically for facilities that cannot capture false negative cancers, which is the documented reason interval cancers sit outside this equation3.
The published instrument
The PPV-recall diagram
Blanks, Moss, and Wallis plotted positive predictive value against referral rate and drew cancer detection rate as isobars across the field2. Every curved line is a constant detection rate. Your practice is the marker. Move any slider and watch it travel.
The shaded box marks the original acceptable performance criteria, a recall rate of 5% to 12% with PPV1 of 3% to 8%13. A BCSC expert panel later widened this, accepting recall rates of 3% to 20% where cancer detection rate reaches 6 per 1,0003. Dutch investigators applied this diagram to reading unit performance across a decade of national screening audit data and found it suitable for monitoring and recommendation13.
Formulas and definitions
What separates PPV1, PPV2, and PPV3
All three answer the same clinical question at three different moments. The distinction lives in where the patient had reached when we stopped to count, and each of those moments is governed by a different part of your operation.
Written out, the three formulas are nearly identical. Each is a true positive count divided by that same true positive count plus a false positive count, times one hundred. The true positive definition never changes: a tissue diagnosis of cancer within one year of a positive examination. One rule, applied three times, to three different groups of patients.
Each false positive means the same thing at its own stopping point: a positive finding whose completed workup resolved as negative. What differs is which examinations are in the denominator, and therefore where the answer has to be found14.
What changes is the false positive. FP1, FP2, and FP3 are filtered against three different events, so the same patient can be an FP1 and never become an FP2, or be an FP2 and never become an FP3. That filtering is the entire difference between the three measures.
- Tissue diagnosis of cancer within one year of a positive examination.1
- FP1 the filter
- A positive screening assessment, meaning BI-RADS 0, 3, 4, or 5, with no known tissue diagnosis of cancer within one year.1
The widest of the three denominators. It holds every positive screening finding whose outcome is known, whichever of the four categories opened it.
- Tissue diagnosis of cancer within one year of a positive examination.1
- FP2 the filter
- A recommendation for tissue diagnosis or surgical consultation, meaning BI-RADS 4 or 5, with no known tissue diagnosis of cancer within one year.14
Narrower, because the diagnostic workup has already resolved most of the recall cohort. Only findings that earned a tissue recommendation are counted here.
- Tissue diagnosis of cancer within one year of a positive examination.1
- FP3 the filter
- A performed biopsy returning a concordant benign tissue diagnosis, or discordant benign tissue with no known cancer diagnosis, within one year.112
Narrowest of the three, and the only one built from pathology reports rather than from assessments. A procedure was documented and a result came back.
Notice what the numerator and the denominators have in common. Cancers arrive on their own. Pathology is returned, registries match, and the true positive count assembles itself.
The false positives do not. FP1 requires the outcome of every positive screening finding. FP2 requires knowing which tissue recommendations resolved negative, including the ones acted on somewhere else. FP3 requires the benign pathology reports in hand. Three separate reconciliation jobs, one for each denominator, and none of them arrives by itself.
Where each measure sits in the pathway
| Measure | Where we stopped to ask | What it tests | Who controls it | Published range |
|---|---|---|---|---|
| PPV1 Abnormal interpretation |
At the positive screening finding, meaning BI-RADS 0, 3, 4, or 5 | The yield of the recall decision. How productive is a callback from screening? | Interpreting physician, at the screening read | 3% to 8%1 |
| PPV2 Biopsy recommended |
When tissue sampling was recommended, meaning BI-RADS 4 or 5 | The precision of the referral decision after diagnostic workup. | Interpreting physician, at the diagnostic read | 20% to 40%1 Screening table. Diagnostic table gives 15% to 40% for workup of abnormal screening |
| PPV3 Biopsy performed |
When the biopsy was completed and the pathology result returned | Real-world tissue yield, after patients comply and results return. | Scheduling, navigation, and result capture, jointly | 20% to 45%1 Diagnostic table, workup of abnormal screening |
Notice the last column. PPV1 and PPV2 are largely tests of interpretive judgment. PPV3 is not. By the time a case reaches the PPV3 denominator, it has passed through scheduling, patient compliance, procedural completion, and pathology reporting. A practice can read beautifully and still post a poor PPV3, and the audit will not tell you which one broke.
One point on the numerator, because it surprises people. The same true positive count appears in all three formulas. The ACR writes TP without a subscript in every one of them, and puts the subscript on the false positive term instead1. What separates the three measures is entirely which examinations fall into the denominator, and therefore which non-cancer outcomes are counted as false positives.
Benchmarks
How these thresholds are applied in a Mammologix audit
The color scoring used in the Mammologix KPI Analysis and Clinical Performance Review is shown below. These bands are the Mammologix applied scoring methodology, shown for transparency rather than as a published standard, and Mammologix sells the audit service that uses them. Positive predictive value carries no upper penalty. A value above the published range is still scored favorably, though it deserves a look at the denominator before anyone celebrates.
| Metric | Below benchmark | Within benchmark | Exceeds benchmark | Ref |
|---|---|---|---|---|
| Annual mammogram volume Screening and diagnostic combined |
Under 480 per year | 480 or more, below practice average | At or above practice average | 14 |
| Recall rate | Over 12%, or 0.1% to 3.9% | 10.1% to 12% | 4% to 10% | 17 |
| PPV1 | Under 3% | 3% or higher no amber tier applied | 17 | |
| Cancer detection rate | Under 2.5 per 1,000 | 2.5 or more, below practice average | At or above practice average | 17 |
| PPV2 | Under 20% | 20% or higher no amber tier applied | 17 | |
| PPV3 | Under 20% | 20% or higher no amber tier applied | 1 | |
| Sensitivity Screening |
Under 75% | 75% to 89.9% | 90% or higher | 114 |
| Specificity Screening |
Under 88% | 88% to 91.9% | 92% or higher | 17 |
Methodology
Frequently asked questions
Why is PPV1 so much lower than PPV2 and PPV3?
Because the denominator is far larger. PPV1 counts every patient recalled from screening, and most recalls resolve as benign at diagnostic workup. That is the intended design of screening. PPV2 counts only the cases that survived the diagnostic workup and earned a biopsy recommendation, a much smaller and much more suspicious group. The rise from PPV1 to PPV3 reflects successful filtering, not improving skill.
What makes a screening mammogram positive?
An assessment that requires the patient to come back. BI-RADS 0, 3, 4, and 5 are all positive, and all four are recalls1. What differs is the timing and the purpose.
Category 0 is incomplete and recalls the patient for additional imaging. Category 3 is probably benign and recalls her at a four to six month interval for surveillance. Categories 4 and 5 recall her immediately for an interventional procedure. Categories 1 and 2 are negative and appear in no denominator here.
One nuance that catches people out. A BI-RADS 3 assigned at a diagnostic examination is doing different work than one assigned at screening. At diagnostic it usually functions as a benign finding that returns the patient to her routine schedule, because the workup has already happened and the interpreting physician found no reason for immediate action.
Which BI-RADS categories belong in each denominator?
PPV1 uses all positive screening assessments, meaning BI-RADS 0, 3, 4, and 51. PPV2 uses cases assessed BI-RADS 4 or 5 with tissue sampling recommended. PPV3 uses the subset of those recommendations where a biopsy was actually completed. BI-RADS 1 and 2 are negative assessments and appear in none of the three denominators.
Can PPV3 ever be lower than PPV2?
It is uncommon. PPV3 has the smaller denominator, since a biopsy is performed only where one was recommended, so the same cancer count divided by fewer cases usually produces a higher value.
Where the ordering reverses, the cause is normally a difference in which cases each count could capture. A recommendation acted on at another facility belongs in the PPV2 denominator, because the recommendation was made here. It cannot appear in PPV3 unless the pathology report reaches you4.
Is PPV2 a screening measure or a diagnostic one?
Both, with a variant definition for screening. The ACR designs PPV2 to evaluate diagnostic examinations, since a tissue recommendation normally comes from the diagnostic read1.
When PPV2 is reported for a screening practice, the positive examination is the screening exam itself. That means either the rare BI-RADS 4 or 5 assigned at screening, or a BI-RADS 0 followed by a diagnostic examination that recommends tissue diagnosis for the same lesion1. The patient is tracked forward from her screening exam.
The Atlas adds a caution worth repeating. Screening PPV2 measures screening practice in general rather than the individual screening interpreter, because the tissue recommendation may be made by a different physician at the diagnostic examination1. This calculator models that screening pathway.
Should diagnostic examinations be included?
Not in the PPV1 denominator. PPV1 is a screening measure and its denominator is limited to screening assessments. PPV2 and PPV3 draw from the diagnostic pathway, since a biopsy recommendation is generally issued after the diagnostic workup that follows a recall. Mixing screening and diagnostic populations in a single PPV1 calculation makes the result impossible to benchmark. This matters for PPV2 and PPV3 as well. The ACR publishes a separate diagnostic table: for workup of abnormal screening, PPV2 is 15% to 40% and PPV3 is 20% to 45%, while for a palpable lump the same measures run 25% to 50% and 30% to 55%1. The BCSC observed values for diagnostic digital mammography are PPV2 27.5% and PPV3 30.4%9. Comparing a diagnostic-derived value against a screening range will misread the practice.
What time window applies to cancer confirmation?
Twelve months from the index examination is the standard audit window. A cancer confirmed inside that window counts as a true positive for the examination that flagged it. This is also the reason an audit period needs time to mature111. Calculating positive predictive value on a period that closed last month will understate every one of the three measures, because the outcomes have not arrived yet.
Does a high positive predictive value mean the practice is performing well?
Not on its own. A practice that recalls almost nobody will post an excellent PPV1 while missing cancers, because it only recalls the obvious ones. Positive predictive value has to be read alongside cancer detection rate, abnormal interpretation rate, and sensitivity. Any single audit metric read in isolation can be made to look good by degrading a different one.
Where does the PPV3 range come from?
From the diagnostic table, not the screening table. The ACR BI-RADS Atlas gives acceptable ranges for screening mammography covering cancer detection rate, abnormal interpretation rate, PPV1, PPV2, sensitivity, and specificity. PPV3 is not among them1.
It appears instead in the diagnostic mammography table, where workup of abnormal screening carries a PPV3 range of 20% to 45% and evaluation of a palpable lump carries 30% to 55%1. That placement is logical. A biopsy is performed after a diagnostic workup, so PPV3 is a diagnostic measure even when the patient entered through screening. This calculator models the screening pathway through workup, so it applies the 20% to 45% range.
Two cautions. Read PPV3 against the column that matches how the patient arrived, since a palpable lump cohort is held to a higher standard. And note that the BCSC charts PPV3 without shading an acceptable region6, so the ACR range is the one with a published number behind it.
Where do the false positive counts actually come from?
Not from one place, which is why this is the part of the audit that takes the work. The cancer count largely assembles itself: pathology comes back, registries match, and a tissue diagnosis is hard to miss.
Each false positive has to be built. FP1 requires an outcome for every positive screening finding, and those findings sit on three different clocks. A BI-RADS 0 resolves at the diagnostic workup, a BI-RADS 3 resolves at a four to six month interval return, and a BI-RADS 4 or 5 resolves at tissue diagnosis1. FP2 requires knowing which tissue recommendations came back negative, including recommendations a patient acted on somewhere else. FP3 requires the benign pathology reports themselves112.
A count that is missing cases is not neutral. It reduces the denominator, which raises the positive predictive value, so an incomplete false positive count reads as better performance rather than as missing data.
Quality improvement
Reading a positive predictive value that looks wrong
If your PPV is below the range
- Confirm the denominator first. A PPV2 below 20% is frequently a pathology capture failure rather than an over-referral pattern.
- Check PPV3 against the diagnostic range of 20% to 45%1, and confirm biopsy capture completeness before reading a low value as a referral problem.
- Count how many recommended biopsies have no documented outcome, then recalculate with those cases excluded.
- Check whether BI-RADS 3 assessments issued at screening are being coded into the positive cohort correctly.
- Compare PPV1 against the abnormal interpretation rate. A low PPV1 paired with a high AIR points toward recall threshold, not tracking.
- Review a sample of benign biopsy results against the imaging findings that prompted them, looking for repeated finding types.
If your PPV is above the range
- A high PPV is scored favorably, but verify it is not the product of an unusually small denominator.
- Cross-check the abnormal interpretation rate. A PPV1 well above 8% often accompanies a recall rate below 5%, which raises an underdetection question23.
- Confirm cancer detection rate is at or above 2.5 per 1,0001. Strong PPV with weak CDR suggests cancers are being missed at the screening read.
- Verify that negative and benign cases are being captured completely. Missing benign outcomes inflate PPV the same way missing malignant outcomes deflate it.
- Confirm which modality the cohort represents. Benchmarks differ between digital mammography and digital breast tomosynthesis78.
- Check interpreting physician volume. Small annual volumes produce unstable percentages in either direction3.
Where the work is
The cancers find you. The false positives do not.
Every number on this page divides one count by another. The numerator is the easier of the two. A tissue diagnosis of cancer generates pathology, enters a registry, and is difficult to overlook. Most facilities can produce their cancer count.
The denominators are the work, and there are three of them, assembled from three different places on three different clocks.
What each false positive requires
Why the clocks matter
- A BI-RADS 0 resolves when the diagnostic workup is read.
- A BI-RADS 3 resolves at a four to six month interval return.
- A BI-RADS 4 or 5 resolves at tissue diagnosis.
- All three sit inside one PPV1 denominator, and the audit period has to be mature enough for each to have come due11.
This is why a positive predictive value is a harder number than it looks. The arithmetic takes a second. The correlation behind it is a year of tracking, across categories that resolve on different schedules, at facilities that may not be yours.
Which leaves the question this calculator cannot answer for you. You can see what the formula needs. How would your facility produce those three numbers?
Sources
References
- ACR BI-RADS Atlas, Breast Imaging Reporting and Data System, 5th edition. American College of Radiology; 2013. Follow-up and Outcome Monitoring section. Source of the assessment categories and the true positive and false positive definitions. Table 7 gives acceptable ranges for screening mammography: cancer detection rate at or above 2.5 per 1,000, abnormal interpretation rate 5% to 12%, PPV1 3% to 8%, PPV2 20% to 40%, sensitivity at or above 75%, specificity 88% to 95%. Table 8 gives acceptable ranges for diagnostic mammography, including PPV3 at 20% to 45% for workup of abnormal screening and 30% to 55% for a palpable lump. View source
- Blanks RG, Moss SM, Wallis MG. Monitoring and evaluating the UK National Health Service Breast Screening Programme: evaluating the variation in radiological performance between individual programmes using PPV-referral diagrams. J Med Screen. 2001;8(1):24-28. Establishes that cancer detection rate is the product of positive predictive value and referral rate, and introduces the PPV-referral diagram. View source
- Miglioretti DL, Ichikawa L, Smith RA, et al. Criteria for identifying radiologists with acceptable screening mammography interpretive performance based on multiple performance measures. AJR Am J Roentgenol. 2015;204(4):W486-W491. View source
- Breast Cancer Surveillance Consortium. BCSC Data Definitions, version 3; 2020. Defines FP2 and FP3, and documents that the BCSC does not capture every biopsy, so the PPV2 and PPV3 denominators may differ. View source
- Radiologist characteristics associated with interpretive performance of screening mammography: a National Mammography Database study. Radiology. 2021. Reports acceptable ranges used in the study and gives a PPV3 distribution for screening radiologists with a 25th to 75th percentile of 20.0% to 35.6%, shown here as a secondary comparison. View source
- Breast Cancer Surveillance Consortium. Screening performance benchmarks, performance measures. Documents which measures carry an acceptable performance range and which do not. View source
- National performance benchmarks for modern screening digital mammography: update from the Breast Cancer Surveillance Consortium. Radiology. 2017. View source
- National performance benchmarks for screening digital breast tomosynthesis: update from the Breast Cancer Surveillance Consortium. Radiology. 2022. View source
- National performance benchmarks for modern diagnostic digital mammography: update from the Breast Cancer Surveillance Consortium. Radiology. 2017. Reports PPV3 of 30.4% for diagnostic digital mammography. View source
- Linver MN, Osuch JR, Brenner RJ, Smith RA. The mammography audit: a primer for the Mammography Quality Standards Act (MQSA). AJR Am J Roentgenol. 1995;165(1):19-25. View source
- Funaro K, et al. Understanding the mammography audit. Radiol Clin North Am. 2021. View source
- Institute of Medicine and National Research Council. Improving Breast Imaging Quality Standards. Glossary. National Academies Press; 2005. States the PPV2 and PPV3 formulas in true positive and false positive notation. View source
- Geertse TD, Tetteroo E, Smid-Geirnaerdt MJA, Duijm LEM, Pijnappel RM, van der Waal D, Broeders MJM. Applying the "positive predictive value-recall diagram" to monitor performance and provide recommendations for screening radiologists. Eur Radiol. 2025 Sep 4. doi:10.1007/s00330-025-11978-3. Retrospective evaluation applying the Blanks diagram to reading unit performance using Dutch national screening audit datasets from 2010 to 2019. View source
- Mammography Quality Standards Act and Program. U.S. Food and Drug Administration. Medical outcome audit requirement at 21 CFR 900.12(f). View source
- Newell MS, Destounis SV, Leung JWT, DeMartini WB, Lee CH, Eby PR. ACR BI-RADS v2025 Manual. Reston, VA: American College of Radiology; 2025. Released December 2025 as an extension of the 5th edition. Renames the audit section Auditing and Outcomes Monitoring and recommends either a Basic Clinically Relevant Audit or a More Complete Audit. View source
Standard this tool is built to
Definitions, formulas, and acceptable ranges on this page follow the ACR BI-RADS Atlas, 5th edition1, which remains the basis for the screening mammography medical outcome audit as performed under MQSA14.
The ACR released the BI-RADS v2025 Manual in December 2025 as an extension of the 5th edition rather than a replacement15. It renames the audit section to Auditing and Outcomes Monitoring and recommends either a Basic Clinically Relevant Audit or a More Complete Audit. PPV1, PPV2, and PPV3 carry forward under both.
One v2025 change is worth flagging for anyone auditing beyond screening mammography. In the extent-of-disease breast MRI audit, PPV2 and PPV3 are calculated across distinct BI-RADS 4 or 5 findings rather than examinations, while the abnormal interpretation rate stays at the examination level. This calculator is examination-based and scoped to screening mammography. Do not use it to reproduce a finding-level MRI audit.
BI-RADS is a registered trademark of the American College of Radiology.
Beyond the calculator
Your positive predictive value is only as honest as your denominator.
Mammologix keeps the MQSA medical outcome audit organized year round, tracking follow-up, documenting pathology correlation, verifying BI-RADS outcome data, and keeping KPI reporting current so nobody is assembling records under deadline pressure.
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