The math of invasive breast cancer risk for LCIS

Posted by elsie37 @elsie37, Mar 30, 2019

Lobular Cacrinoma in Situ (LCIS) confers a risk of invasive breast cancer of about 2% a year, maybe a little less, when chemoprovention endocrine meds are NOT taken. If meds are taken, the risk is cut in about half, maybe even cut a little more, so 1% or less.

Furthermore, LCIS is a lifetime risk. That means any 40 year old woman diagnosed with LCIS who could expect to live until 85 has a lifetime risk of 2%/year x 45 more years of life = 90% lifetime risk of cancer. Let's say the risk is only 1.5% per year, to be wildly optimistic and not 2%, since some studies have indicated the annual risk is less than 2%. Then that comes out to a 67.5% lifetime risk, still a big number. (1.5%/year x 45 more years of life)

Other sources show a lifetime risk of developing invasive breast cancer with LCIS to be 20% with some showing up to 35%. Those results do not come out to 2%/year for most women, unless the diagnosis is made at around 65 years or older.

Examples: Age 65 at diagnosis with life expectancy of 85 years means if using even the lower 1.5%/year risk, it is 1.5%/year x 20 more years of life = 30% lifetime risk. Age 70 at diagnosis with life expectancy of 85 years, again using the 1.5% figure is 1.5%/year x 15 more years = 22.5% lifetime risk.

Even the halved annual risk of 1% over a lifetime that may be obtained by taking chemoprovention endocrine meds still does not add up to a halved 10%-18% (instead of 20%- 35%) life time risk of invasive breast cancer,

Example: LCIS diagnosis at age 40 with life expectancy of 85. 1%/year x 45 years to reach age 85 = 45% lifetime risk. While better than even odds for a 40-year old, I think many women would consider something that close to 50% of getting cancer to be too high, especially after investing 5-10+ years of taking risk-reducing drugs, which produce substantial side effects for many. But a diagnosis at age 55 with a 1% annual risk due to medications, would result in a 30% lifetime risk, if life expectancy was 85. (1%/year x 30 years = 30%)

Interestingly, I have repeatedly seen that of all the LCIS diagnoses, only 10%-20% are in women past menopause, so using ages 55-75 for examples to make the annual risk come out similar as lifetime risk does not reflect the reality of who has the most cases of LCIS. I have also read that the number of post-menopause LCIS cases, though now a minority, is growing. And I am one.

Some of us have high hopes of making it to 90+ if we've had many relatives who have lived that long, so that means that 2%/year (or the more optimistic 1.5% or even the 1% with drugs) really makes lifetime risk soar upward.

For women diagnosed in their 30s, or younger, those 2%s accumulate over an even longer period, so that the odds of invasive cancer could easily reach 100% over a lifetime. Or more, but of course that is not possible. However, no studies I have found warn of guaranteed invasive breast cancer (100%) for those with LCIS if you live long enough.

Something does not add up. Perhaps it is the mathematician, (me). Or my LCIS assumptions are wrong. Maybe risk does not increase in a linear fashion year after year, maybe it tapers off? It seems to me that either all the lifetime risk numbers out there from reputable sources are wrong or the 2%/year over a lifetime (halved or more with medication) is wrong. So that those of us with LCIS can decide what treatment is best, we need to know which numbers are right--and which are wrong.

Can the Mayo experts or the moderator or another poster shed some light? Thank you in advance.

Interested in more discussions like this? Go to the Breast Cancer Support Group.

Wow! I just followed a thread through this site and realized this discussion was going on while I had just finished radiation and started on anastrozole. I had LCIS diagnosis at age 49. I took tamoxifen for 5 years and 9 years later was diagnosed with invasive lobular.

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@elsie37
I have a math background and find the statistics for cancer hard to understand. (Which I'd never looked at, coming from a cancer-free family, until a bad news biopsy last year led to a lumpectomy.)

Here's one example that makes no sense. Two oncologists I saw said that the rule of thumb is that taking an aromatase inhibitor could [note: "could".] lower my risk of recurrence by approximately 45% in general. But that was before the OncotypeDX showed a risk of recurrence of approximately 5.5% if I didn't take them so I didn't have the 'industry accepted' higher risk that the 45% 'could' lower.

The rule of thumb of 45% risk reduction in favor of aromatase inhibitors for ER+, PR+, HER2- breast cancers is usually rounded up to 50% as it's easier to quote.

BUT, one article in the respected New England Journal of Medicine by an oncologist, a leader in his field, noted that the NNT number (aka 'number needed to treat' to prevent projected cancer) for aromatase inhibitors is 49. And his point was that it's a serious ethical question of whether 48 women should be told to take a 'toxic' (his word) drug that they may not even benefit from. And that patients should be fully informed of the side effects and statiscally-derived likely benefit so each can decide whether to take them. And that failing to adequately inform breast cancer patients is further fostering the environment of patient non-compliance or, worse, loss of confidence in physicians at a time when they most need to have it.

What bothers me is that 1 in 49 does not yield a statistic anywhere near the 45% risk reduction talked about. So how does 1 in 49, rounded to 2%, become that near-50%?

I have an M.B.A. in finance and am used to double-checking pro forma numbers and too-rosy projections so this caught my attention and I've not yet found the explanation unless there's some arcane stat to explain it, e.g., the drugs prevent 100% of recurrences for some kind of cancer that accounts for, say, 70+% of cancers to bring the mean (average) risk reduction up to 45-50%?

I'm sure there are benefits (and known downsides) to aromatase inhibitors. But getting clean data points to connect and base a decision on is oddly difficult.

I skipped the drugs. A friend asked if, if I suffer a recurrence, I'll think that not taking them caused it. And, upon thinking it over, my answer would be no. I'd have a 3% risk of recurrence if I'd done the trifecta of radiation, chemo and adjuvant anti-hormone therapy (and get osteoporosis from the latter, at a minimum). So I'd never know what 'caused' the recurrence except that something is very wrong when 1 in 8 women in this country is predicted to get breast cancer in her lifetime in the first place...

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This is disconcerting because LCIS isn’t usually found until there’s been a biopsy for another reason?

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@abartels

No one in my family had cancer until they were in their 70s. I did not test positive either. When I was 40 I had a ductile lavage after lumpectomy. They felt that I had 7 to 8 years of being clear. At that time they said I was 2 stages away from cancer. It was up to me take the Tamoxifen. I did not. 8 years later it was found on a MRI, 3 months after a mammogram at Stage 0. MRI Had caught it very early. I took Tamoxifen for 4 1/2 years until I had a black blood clot.

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Any side effects from Tamoxifen?

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@rarelybees2889

Mammeogram next week. Let's hope all is well.

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Fingers crossed!

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@lisakinpa

This is disconcerting because LCIS isn’t usually found until there’s been a biopsy for another reason?

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Yes, thats true. Its not a common find either, being rare.
Luckily I have had no problems or cancer develop from watchful waiting. Tamoxifen has some very bad side effects, including cognitive issues. Plus removing all estrogen is not great for the body, if one doesn't actually have breast cancer and LCIS is not cancer.
I did a lot of research on the drug and felt awful on it.
We need better safer options for LCIS and other neoplasms and more research on what our risks really are.

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It would be nice if some doctor would weigh in.
I go to Mayo.
I also have tried to figure it out and I agree, something just doesn't mesh with the risk factors used. I went from 70 % to 25-30% based on the a different model? WOW. and the stress of thinking I had 70% chance was not great either.
I think there is a big need for better quality research.
I am not a fan of the scare tactics used sometimes either.

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I’m not sure if the numbers compound each and every year?

I went onto the Mayo website which gives a 20% chance of receiving a breast cancer diagnosis if a patient has LCIS. ♥️

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@callalloo

@elsie37
I have a math background and find the statistics for cancer hard to understand. (Which I'd never looked at, coming from a cancer-free family, until a bad news biopsy last year led to a lumpectomy.)

Here's one example that makes no sense. Two oncologists I saw said that the rule of thumb is that taking an aromatase inhibitor could [note: "could".] lower my risk of recurrence by approximately 45% in general. But that was before the OncotypeDX showed a risk of recurrence of approximately 5.5% if I didn't take them so I didn't have the 'industry accepted' higher risk that the 45% 'could' lower.

The rule of thumb of 45% risk reduction in favor of aromatase inhibitors for ER+, PR+, HER2- breast cancers is usually rounded up to 50% as it's easier to quote.

BUT, one article in the respected New England Journal of Medicine by an oncologist, a leader in his field, noted that the NNT number (aka 'number needed to treat' to prevent projected cancer) for aromatase inhibitors is 49. And his point was that it's a serious ethical question of whether 48 women should be told to take a 'toxic' (his word) drug that they may not even benefit from. And that patients should be fully informed of the side effects and statiscally-derived likely benefit so each can decide whether to take them. And that failing to adequately inform breast cancer patients is further fostering the environment of patient non-compliance or, worse, loss of confidence in physicians at a time when they most need to have it.

What bothers me is that 1 in 49 does not yield a statistic anywhere near the 45% risk reduction talked about. So how does 1 in 49, rounded to 2%, become that near-50%?

I have an M.B.A. in finance and am used to double-checking pro forma numbers and too-rosy projections so this caught my attention and I've not yet found the explanation unless there's some arcane stat to explain it, e.g., the drugs prevent 100% of recurrences for some kind of cancer that accounts for, say, 70+% of cancers to bring the mean (average) risk reduction up to 45-50%?

I'm sure there are benefits (and known downsides) to aromatase inhibitors. But getting clean data points to connect and base a decision on is oddly difficult.

I skipped the drugs. A friend asked if, if I suffer a recurrence, I'll think that not taking them caused it. And, upon thinking it over, my answer would be no. I'd have a 3% risk of recurrence if I'd done the trifecta of radiation, chemo and adjuvant anti-hormone therapy (and get osteoporosis from the latter, at a minimum). So I'd never know what 'caused' the recurrence except that something is very wrong when 1 in 8 women in this country is predicted to get breast cancer in her lifetime in the first place...

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May I suggest you have your oncologist further explain the significance of your Oncotype DX numbers? My risk of recurrence was listed as 7%, but that was only if I took an aromatase inhibitor every day for 7 years.

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@callalloo

@elsie37
I have a math background and find the statistics for cancer hard to understand. (Which I'd never looked at, coming from a cancer-free family, until a bad news biopsy last year led to a lumpectomy.)

Here's one example that makes no sense. Two oncologists I saw said that the rule of thumb is that taking an aromatase inhibitor could [note: "could".] lower my risk of recurrence by approximately 45% in general. But that was before the OncotypeDX showed a risk of recurrence of approximately 5.5% if I didn't take them so I didn't have the 'industry accepted' higher risk that the 45% 'could' lower.

The rule of thumb of 45% risk reduction in favor of aromatase inhibitors for ER+, PR+, HER2- breast cancers is usually rounded up to 50% as it's easier to quote.

BUT, one article in the respected New England Journal of Medicine by an oncologist, a leader in his field, noted that the NNT number (aka 'number needed to treat' to prevent projected cancer) for aromatase inhibitors is 49. And his point was that it's a serious ethical question of whether 48 women should be told to take a 'toxic' (his word) drug that they may not even benefit from. And that patients should be fully informed of the side effects and statiscally-derived likely benefit so each can decide whether to take them. And that failing to adequately inform breast cancer patients is further fostering the environment of patient non-compliance or, worse, loss of confidence in physicians at a time when they most need to have it.

What bothers me is that 1 in 49 does not yield a statistic anywhere near the 45% risk reduction talked about. So how does 1 in 49, rounded to 2%, become that near-50%?

I have an M.B.A. in finance and am used to double-checking pro forma numbers and too-rosy projections so this caught my attention and I've not yet found the explanation unless there's some arcane stat to explain it, e.g., the drugs prevent 100% of recurrences for some kind of cancer that accounts for, say, 70+% of cancers to bring the mean (average) risk reduction up to 45-50%?

I'm sure there are benefits (and known downsides) to aromatase inhibitors. But getting clean data points to connect and base a decision on is oddly difficult.

I skipped the drugs. A friend asked if, if I suffer a recurrence, I'll think that not taking them caused it. And, upon thinking it over, my answer would be no. I'd have a 3% risk of recurrence if I'd done the trifecta of radiation, chemo and adjuvant anti-hormone therapy (and get osteoporosis from the latter, at a minimum). So I'd never know what 'caused' the recurrence except that something is very wrong when 1 in 8 women in this country is predicted to get breast cancer in her lifetime in the first place...

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Often the numbers you read are from research of different sources. You might want to consider that research results will be different as it is taken from different research that won’t be the same just as individual people are different. You might think of it this way: Research results will show different outcomes due to the individuals who are studied having many differences on the whole for instance perhaps where they live. You won’t find the exact numbers of such things on the results of different research. For just one small example from a research project might be based on participants being primarily male with ages up to fifty and what were the participants exposed to, what known illnesses were present in their family members, etc. Research cannot include all participants who have exactly the same ancestors, background, other illnesses and exposures. Good research is going to show different results and new questions, but somewhere something will come up in research that can be useful. That may then lead us pointing into another direction to implement toward cause or cure.

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