FAQs: Probability of Causation (POC)
The Department of Labor (DOL) is responsible for determining the probability that a cancer included in a claim under EEOICPA (The Act) was caused by workers’ exposure to radiation during nuclear weapons production. DOL will determine the “probability of causation” for each claim for which NIOSH is required to complete a dose reconstruction. Generally, with some exceptions, these claims are for workers who are not a member of the Special Exposure Cohort.
To find answers to your questions about Probability of Causation, click any one of the questions listed below to view its answer.
Probability of Causation
What is "probability of causation"?
Under EEOICPA (The Act), probability of causation is a measure of how likely it is that an energy employee's cancer was "at least as likely as not" caused by occupational exposure to ionizing radiation.
What does dose reconstruction have to do with the probability of causation?
The Department of Labor (DOL) will use the energy employee's personal characteristics, employment, medical information, and dose reconstruction results developed by NIOSH to determine the probability of causation.
What is the Probability of Causation rule?
This rule provides the guidelines that DOL uses to determine the degree of likelihood that a cancer included in a case was "at least as likely as not" caused by the energy employee's exposure to radiation during nuclear weapons production.
Where can I find a copy of the Probability of Causation rule?
How is probability of causation calculated under EEOICPA (The Act)?
NIOSH developed a computer program that is used by DOL to determine the probability of causation. The computer program, known as NIOSH-IREP, uses cancer risk models developed primarily by the National Cancer Institute (NCI) to estimate the probability of causation under The Act.
The risk models take into account the energy employee's cancer type, year of birth, year of cancer diagnosis, exposure information (years of exposure, radiation type, and dose). Smoking history is taken into account for lung cancer cases. Ethnicity is taken into account for skin cancer cases. Under Part B of the Act, exposures to other occupational, environmental, or dietary carcinogens are not currently taken into consideration for the probability of causation calculation.
What is the significance of the probability of causation calculation?
Probability of causation is expressed as a percentage between 0 and 100. A value of 100% means that it is certain that the radiation dose was the cause of the cancer. A value of 0% means that it is certain that the radiation dose was not the cause of the cancer. As defined in The Act, probability of causation values greater than or equal to 50% at the upper 99th percentile credibility limit mean that it is "at least as likely as not" that the radiation dose caused the energy employee's cancer. Therefore, if the probability of causation for your case is less than 50%, you will not be entitled to compensation. If your probability of causation is between 50% or greater, DOL will recommend that you receive compensation.
Does NIOSH determine/calculate the percent that determines the compensability of the claim?
No, NIOSH reconstructs a worker's radiation dose and determines a final estimate of the worker's exposure to radiation. The results from a worker's dose reconstruction are sent to DOL. DOL determines the probability of causation – the likelihood that the worker's cancer was related to radiation exposure received while employed at a covered facility.
What is uncertainty?
A term used to describe the lack of precision and accuracy of a given estimate, the extent of which depends upon the amount and quality of the evidence or data available.
What are some examples of uncertainty?
Some statistical issues associated with epidemiological studies (e.g., possible measurement error, possible effects of confounding variables, etc) are:
- Amount of radiation exposure
- Dose-response assumptions
- Transfer of "excess risk" from Japanese and other exposed populations to EEOICPA claimant population
What is the effect of uncertainty on the probability of causation?
- Uncertainty is built into nearly every part of the process of estimating causation
- Uncertainty distributions are used in dose reconstruction, cancer risk models, etc.
- "Credibility limits" are placed around the central estimate of PC
- Upper 99th percentile determines final PC result and claim outcome
- An accounting of uncertainty is necessary because the upper 99% credibility limit of PC is used in adjudicating claims for compensation
- Uncertainty is often a major contributor to PC
What is an uncertainty distribution?
A range of discrete or continuous values arrayed to encompass, with high confidence, the true but unknown values of a given quantity or parameter.
What is the Upper 99th percent credibility limit?
The Upper 99th percent credibility limit is the 99th percentile of the range of values in an uncertainty distribution. The uncertainty distribution of the probability of causation (PC) is first estimated, and the upper 99th percentile of this distribution is compared to the decision criterion (a PC of 50%) to determine eligibility for compensation.
What factors could influence the probability of causation result?
- Dose reconstruction efficiency process
- Erring on the side of the claimant
- During case development by DOL
- Selection of IREP cancer model: policy often requires running 2 or more models and using the highest PC
- Use of NIOSH-IREP "combined" lung cancer risk model
- Handling of "unknown primary" cancers
- Handling of claims with more than one primary cancer
- Special "multiple primary" equation increases the likelihood of compensation.
- NIOSH-IREP cancer risk models
- Personal characteristics: gender, age at exposure, age at diagnosis, latency, smoking history, ethnicity
- Reconstructed radiation dose: organ dose, radiation type, radiation energy, exposure rate
- Uncertainty: in cancer risk models, in dose
- Policy: multiple primary cancers, unknown primary cancer, alternate cancers
How does NIOSH calculate the probability of causation when a claim has more than one primary cancer?
- NIOSH-IREP includes a procedure to calculate an upper 99% credibility limit of PC when a claim for compensation involves more than one primary cancer.
In all these cases, NIOSH-IREP is run for each primary cancer separately, and the upper 99% credibility limit of probability of causation (PC) for all cancers combined is computed based on the upper 99% credibility limits of all the cancers involved, using the Multiple Cancer Equation:
PCtotal = 1 – [(1 – PC1)x(1 – PC2)x…x(1 – PCn)]
I reported new cancers to DOL and they sent my claim to NIOSH for a new dose reconstruction. I received the results from the new dose reconstruction. The probability of causation is even lower than the first dose reconstruction. Why did this happen?
NIOSH understands this concern. It may seem obvious that when additional cancers are added to a dose reconstruction it would increase the probability that radiation caused the multiple cancers. However, in some cases, the NIOSH dose reconstruction will result in a lower probability of causation when additional cancers are added. An explanation for how and why this can happen is as follows:
Accurately estimating the exposure a worker received while working at a covered facility is a time consuming process. In order to complete dose reconstructions in as timely and efficient a manner as possible, NIOSH may make assumptions on dose estimates that are favorable to the claimant in order to simplify the dose reconstruction process.
For instance, instead of completing a dose reconstruction which precisely estimates the worker's exposure for cases that would most likely result in a probability of causation well below the 50% necessary for the claim to be compensable by DOL, NIOSH will significantly over-estimate the exposure based on the highest levels of exposure observed or possible for the facility. If the claim will not be compensable even when using these significantly over-estimated exposure estimates, then no further refinement to the dose reconstruction is required.
This manner of dose reconstruction is called an "efficiency measure." It allows NIOSH to issue a timely dose reconstruction where attempts to refine the exposure estimate would not result in a compensable claim (i.e., a full dose reconstruction would in all likelihood produce a much lower probability of causation than the over-estimated exposure values used).
Anytime a new cancer(s) is reported to NIOSH by DOL, NIOSH is required to rework the dose reconstruction to include the new cancer(s). If the new cancer(s) creates a potentially compensable case, NIOSH must refine the dose reconstruction using more probable and precise exposure estimates and not the significant over-estimates as mentioned above. These new, more accurate exposure estimates will be lower than the original estimate because we no longer use the assumptions which overestimated the radiation dose for the cancer found in the initial dose reconstruction. The revised radiation dose estimate may result in a probability of causation for the new cancer(s) that is lower than the non-compensable estimate that was obtained for the first cancer using the over-estimated radiation exposure. That is why the addition of a new cancer(s) may result in a probability of causation that is lower than the probability found for the single original cancer. However, this does not always occur when a new cancer(s) is added to a claim and NIOSH has to rework the dose reconstruction. It is possible for additional cancer(s) to produce a full dose reconstruction that will be determined to be compensable by DOL.
The use of "efficiency measures" and procedures for dose reconstructions that NIOSH follows under The Act are described in detail in Final Rule: Methods for Radiation Dose Reconstruction under EEOICPA–42 CFR 82 [ PDF 129 KB (23 pages)].
Who do I contact if I have additional questions about probability of causation?
- Page last reviewed: September 28, 2015
- Page last updated: September 26, 2014
- Content source:
- National Institute for Occupational Safety and Health Division of Compensation Analysis and Support