BRCAPRO calculator: BRCA1 and BRCA2 carrier probability from a family pedigree

Short version. BRCAPRO is a Bayesian calculator that takes a family pedigree annotated with breast and ovarian cancer diagnoses and returns the probability the counselee carries a pathogenic variant in BRCA1 or BRCA2, plus projected cumulative cancer risk. It is part of the BayesMendel suite developed at Johns Hopkins and is one of the most widely used and best-validated hereditary cancer risk tools in clinical genetics. Its strengths are focus and validation; its limitations are that it models only BRCA1 and BRCA2 and does not incorporate polygenic risk scores, moderate-penetrance genes, or non-genetic risk factors. For comprehensive breast cancer risk that includes those components, clinicians often use BOADICEA (CanRisk) alongside it; for screening-intensity decisions driven by hormonal and density factors, they often use Tyrer-Cuzick. Evagene runs BRCAPRO directly on the pedigree data you have already drawn, with no re-entry, as part of a broader hereditary cancer risk assessment workflow.

What BRCAPRO is

BRCAPRO is a Bayesian statistical model that estimates the probability an individual carries a pathogenic germline variant in BRCA1 or BRCA2 based on the pattern of breast and ovarian cancer in their family. It was developed as part of the BayesMendel framework at Johns Hopkins in collaboration with Harvard, and is distributed as an open-source R package. It has been referenced in hundreds of clinical guideline documents and research studies, and is one of the original quantitative carrier-probability models in hereditary cancer genetics.

The model's core is straightforward. It starts from a prior probability that the counselee carries a BRCA1 or BRCA2 pathogenic variant, derived from population-specific allele frequencies. It then uses the family pedigree — the affected and unaffected relatives, their ages, their cancer types, and any known genetic test results — to update that prior into a posterior probability. The mathematical machinery is the Elston-Stewart peeling algorithm, which propagates genotype likelihoods through the pedigree efficiently without having to enumerate every possible joint genotype. The output is a calibrated probability that the counselee carries a pathogenic variant, together with projections of future cancer risk conditional on that probability.

BRCAPRO is narrower in scope than more recent multi-gene, polygenic, risk-factor-integrating models. That narrowness is deliberate. Focusing on BRCA1 and BRCA2 with well-characterised penetrance functions gives a statistically clean, reproducible, independently validated tool. When the clinical question is "should this patient be offered BRCA testing, and what does their family history imply about their BRCA1/BRCA2 carrier status?", BRCAPRO is a strong answer.

How BRCAPRO works under the hood

The Bayesian update at the heart of BRCAPRO combines three elements. First, a prior probability of carrying a pathogenic variant, which depends on population allele frequencies. In most European populations the combined BRCA1 and BRCA2 carrier frequency is in the region of 1 in several hundred. In Ashkenazi Jewish populations it is approximately an order of magnitude higher, driven by three well-characterised founder variants (BRCA1 c.68_69delAG, BRCA1 c.5266dupC, and BRCA2 c.5946delT). BRCAPRO uses ethnicity as an input precisely so it can select appropriate priors.

Second, a penetrance function for each gene: the probability of developing breast cancer or ovarian cancer by each age given the genotype. BRCAPRO uses published penetrance functions derived from large family studies, conditional on sex and cancer type. These functions are the reason an unaffected 72-year-old mother reduces the posterior probability of a BRCA1 pathogenic variant — if she carried one, the likelihood she would have developed cancer by 72 is high, so her unaffected status is evidence against a variant segregating through her line.

Third, a likelihood contribution from each relative. For every individual in the pedigree, BRCAPRO computes the likelihood of observing their cancer status and age given each possible genotype. Affected relatives with early-onset breast or ovarian cancer generate strong likelihood ratios that pull the posterior upward. Unaffected elderly relatives generate likelihood ratios below one that pull the posterior downward. Male breast cancer is a particularly strong signal for BRCA2. Bilateral breast cancer strengthens both signals. Prior BRCA test results from the counselee or any tested relative are incorporated directly, with sensitivity and specificity of the test taken into account.

The peeling algorithm runs this computation efficiently across the whole pedigree, returning the posterior carrier probability as the final output.

Required inputs

To run BRCAPRO, you need a structured pedigree containing, for each individual:

• Sex and biological relationship to the counselee.
• Breast cancer status and age at first diagnosis if affected; note bilateral disease and age at contralateral diagnosis.
• Male breast cancer status and age at diagnosis if affected.
• Ovarian cancer status and age at diagnosis if affected.
• Current age if alive and unaffected; age at death and cause of death if deceased.
• Prior BRCA1 and BRCA2 genetic testing results, including variants of uncertain significance if available.
• Self-reported ancestry, specifically whether of Ashkenazi Jewish descent on either parental line.

A minimum three-generation pedigree on both parental sides is the conventional standard. Cancer predisposition genes can be inherited from either parent, so a family history that appears to cluster on the maternal side still requires paternal-side information. See our guidance on breast cancer family history evaluation for the red-flag patterns that make this especially important.

What BRCAPRO outputs

BRCAPRO produces two categories of output. The posterior carrier probability is the probability, given all the pedigree evidence, that the counselee carries a pathogenic variant in BRCA1, in BRCA2, or in either. These three probabilities are reported separately because the two genes have overlapping but distinct cancer risk profiles, and decisions such as which variants to prioritise on a clinical report can hinge on which gene is the stronger candidate.

The cumulative cancer risk projection is the probability of developing breast cancer or ovarian cancer by specified future ages — commonly 50, 60, 70, and 80. These projections are conditional on the estimated carrier status. If the posterior carrier probability is low, the projected risk approaches population baseline; if it is high, the projected risk approaches the penetrance curve for the implied genotype.

Clinical thresholds for action vary by guideline and jurisdiction, but a posterior carrier probability at or above 10 percent is a commonly cited threshold for offering BRCA genetic testing under many national frameworks. The specific threshold depends on local commissioning criteria — NICE in the UK, NCCN in the US, and equivalent bodies elsewhere publish current referral criteria.

Clinical uses

BRCAPRO supports three core decisions in hereditary breast and ovarian cancer clinics. The first is eligibility for genetic testing. Many commissioning frameworks require a documented carrier probability above a threshold before BRCA panel testing is offered. BRCAPRO provides the quantitative evidence required, grounded in published methodology rather than clinician judgement alone.

The second is risk stratification for screening and surveillance. Cumulative risk projections inform whether to recommend enhanced surveillance such as annual breast MRI, the age at which surveillance should begin, and whether risk-reducing surgery conversations are warranted.

The third is cascade testing decisions within the family. A high carrier probability for the counselee implies that first-degree relatives are at a baseline 50 percent risk of inheriting the same variant. Identifying the probable at-risk branches of the family helps target testing resources.

Our broader guide to hereditary cancer risk assessment covers how these decisions fit into the wider genetic counselling workflow, and our ovarian cancer family history page discusses the particular weight that ovarian cancer carries in the BRCAPRO signal.

Limitations of BRCAPRO

BRCAPRO is a focused tool. Its focus is also its limitation, and an honest account matters.

• Two-gene scope. BRCAPRO models BRCA1 and BRCA2. It does not estimate probabilities for moderate-penetrance breast cancer genes such as PALB2, CHEK2, ATM, BARD1, RAD51C, or RAD51D. For those, a multi-gene model such as BOADICEA is required.
• No polygenic risk scores. BRCAPRO does not incorporate polygenic risk scores (PRS) based on common variants. PRS can meaningfully shift predicted risk, particularly for women without a strong monogenic family history.
• No mammographic density or hormonal/reproductive factors. These are important non-genetic risk modifiers, especially for screening-intensity decisions. Tyrer-Cuzick (IBIS) and BOADICEA incorporate them; BRCAPRO does not.
• Pedigree quality dependence. Like any family-history-based model, BRCAPRO is only as accurate as the pedigree. Missing relatives, uncertain ages, and undifferentiated "cancer" without site information all degrade the estimate.
• Penetrance assumptions. Published penetrance functions come from specific cohorts and may not generalise perfectly across all populations or variant classes.

None of these limitations invalidate BRCAPRO. They define where it sits in a modern risk assessment toolkit: a rigorous, focused BRCA1/BRCA2 carrier probability calculator, used alongside other tools for questions it is not designed to answer.

BRCAPRO vs BOADICEA vs Tyrer-Cuzick

The three models most often compared in hereditary breast cancer clinics are BRCAPRO, BOADICEA, and Tyrer-Cuzick. They answer different questions.

In practice, a breast cancer genetics service may run BRCAPRO for a clean BRCA1/BRCA2 carrier probability, BOADICEA for a broader multi-gene plus polygenic plus risk-factor picture, and Tyrer-Cuzick for a lifetime risk estimate that drives screening decisions. The three are complementary. See our pages on BOADICEA alternatives and Tyrer-Cuzick alternatives for more on how clinicians reason about these tools.

How Evagene integrates BRCAPRO

Running BRCAPRO traditionally involves extracting structured family history from whatever system holds it, reformatting it for the BayesMendel R package, invoking the model in R, and bringing the results back into the clinical record. That is work. It is also error-prone: every manual re-entry is a chance to drop a relative, mis-code an age, or misattribute a cancer site.

Evagene runs BRCAPRO directly on the pedigree you have already drawn or imported. The same structured data that powers the pedigree canvas — sex, relationship, cancer diagnoses, ages, vital status, prior test results, ethnicity — is the input BRCAPRO needs. There is no re-entry step. The model executes in an R sidecar process that calls the validated BayesMendel package, so the calculation is the same one peer-reviewed research relies on, not a reimplementation.

Two features extend the basic integration. First, batch risk screening: Evagene can run BRCAPRO, MMRpro, and PancPRO across all catalogued diseases for a given pedigree in a single operation, surfacing conditions where the family history crosses a configurable threshold. This inverts the traditional workflow — rather than the clinician deciding which model to run, the software flags the conditions the clinician should consider. Second, AI interpretation: BRCAPRO results can be passed to an AI-drafted clinical report via bring-your-own-key large language models (Anthropic or OpenAI), producing structured narrative that a clinician reviews and edits. This is a drafting aid, not a replacement for clinical judgement.

For programmatic use, BRCAPRO runs are exposed through the Evagene REST API and MCP server, so a downstream system — an EHR integration, a research pipeline, or an AI agent — can submit a pedigree and retrieve carrier probabilities and cumulative risk estimates without a human in the loop. Documentation is at evagene.net/help. Evagene is browser-based with zero install, and is free during Alpha via the waiting list.

Frequently asked questions

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