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Superseed? Apricot kernels, touted as cancer cure, linked to cyanide poisoning

Author: Catherine Solyom
Date: November 22, 2017
Source: flipboard.com

Brendan Brogan had just returned from a shopping trip on the Plateau laden with exotic snacks.

On a visit to Montreal from California, he stood in the doorway of his buddy Mike Guetta’s room, munching away on something as they discussed the absurdities of the day.

Then Guetta looked up.

“Those better not be almonds,” he said. “You know I’m allergic to those.”

“No, no,” Brogan replied, “I would never do that. These are apricot pits.”

“What?!? Don’t eat those! They’re poisonous!”

Brogan pooh-poohed the warning, arguing the kernels were organic and he’d bought them at the health food store.

“Look! It’s the superseed of the Hunza people, with Vitamin B17!”

Then he turned the bag over and read the fine print. His face went grey: “Caution: Do not consume more than 2-3 kernels per day. Keep out of the reach of children. Pregnant and nursing women should not consume apricot kernels. Health Canada warns that eating too many apricot kernels can lead to acute cyanide poisoning.”

After a quick call to poison control, Brogan rushed to the nearest emergency room. He had eaten a third of the bag.

Apricot kernels, like cherry pits and apple seeds, contain a product called amygdalin, also known as laetrile and marketed as Vitamin B17.

Bitter apricot kernels — the pits of the pits — are widely available in Montreal health food stores, including at Rachelle-Béry branches across the city, where Brogan bought some. They are gluten-free, pesticide-free, vegan and organic.

They are also potentially lethal, as Brogan found out.

The kernels, like cherry pits and apple seeds, contain a product called amygdalin, also known as laetrile and marketed as Vitamin B17, though it’s more like an anti-vitamin.

When the seeds are chewed and digested, the amygdalin is converted to cyanide in the stomach. Eat too much of them — more than three apricot kernels for an adult and just one kernel for a toddler — and cyanide poisoning can occur.

Cyanide cuts off oxygen supply. Symptoms include headache, dizziness, mental confusion, weakness, difficulty breathing, abdominal pain, nausea, vomiting, seizures, coma and, eventually, death.

That’s why Australia, for one, has banned the sale of apricot kernels. But that didn’t stop a Melbourne man from slowly poisoning himself by ingesting 17 mg of homemade apricot kernel extract per day, in the mistaken belief that it would cure his prostate cancer. When doctors performed routine surgery on him in September, they found cyanide levels in his blood that were 25 times the accepted level.

Germany and the United Kingdom have also restricted the sale of apricot kernels, after a number of cases of children hospitalized for cyanide poisoning. In 2011, for example, a 28-month old girl was rushed unconscious to hospital in Turkey. She died in hospital of acute cyanide poisoning 22 days later. She had eaten 10 kernels.

The U.S. Food and Drug Administration has prohibited the sale of apricot kernels if  “intended for use in the cure, mitigation, treatment, or prevention of disease.”

The Canadian Food Inspection Agency, for its part, issued a recall and health hazard alert for Our Father’s Farm brand of apricot kernels in 2009, after a reported case of cyanide poisoning.

Since then the agency has received two more complaints of illness.

Packaging must now carry Health Canada’s warning label. But other brands have filled the void left by Our Father’s Farm.

 

Brogan bought the Organic Traditions brand of the kernel. Manually harvested and imported from Uzbekistan, the kernels are perhaps the “prized superseed” of the Hunza people. It says so right there on the packaging, along with the following claims: “contains vitamin B17” and “used in Ancient Asian medicine for centuries.”

In texts dating back to the 1930s that are rehashed by consumer direct and alternative health websites, the Hunza or Burusho people of the Himalayan region of northern Pakistan are said to live to be 140 and never get sick.

It must be because of the kernels, the story goes.

For example, a Facebook site liked by  997,744 people — titled “The truth about cancer” — says the Hunzas enjoyed near-perfect health.

“Some lived to be over 135 years old and no one in their clan had any of the conditions so common in the modern world, such as diabetes, obesity, heart attack, and cancer.” The website continues in bold lettering, noting that “they ate massive quantities of apricot seed kernels.”

Numerous other websites also claim that apricot kernels can prevent or cure cancer. The kernels are said to treat arthritis, boost your immune system and even serve as an aphrodisiac.

The truth about apricot seeds — and the Hunza people — is less rosy, however. A New York Times reporter who travelled to this Shangri-La in 1996 discovered a beautiful place indeed. But the elderly men who looked to be 140 were probably more like 70.

“The great Hunza secret to old age turned out to be its absence of birth records,” John Tierney wrote.

By  modern accounts, Hunza life expectancy is similar to other people in remote mountain regions who go through cycles of food scarcity — 50 to 60 years old.

On the seeds themselves, the science has been conclusive. Numerous studies show that amygdalin does kill cancer cells — and all other cells too.

Joe Schwarcz, the director of McGill University’s Office for Science and Society, said the initial idea — generating small amounts of cyanide to kill fast-multiplying cancer cells — was not a bad one. But it just doesn’t work, he said.

The sale of apricot seeds “clearly should not be allowed,” he said, surprised at how readily they are found on store shelves in Montreal.

Schwarcz says Health Canada is overwhelmed and useless at stopping the sale of bogus health remedies.

“With dietary supplements, they tend to say well, it’s not really dangerous, and let them be,” Schwarcz said, vowing to confront Health Canada about the sale of the seeds as a vitamin. “But this one is not in that category. You don’t need a lot of these kernels to do a lot of harm.”

A spokesperson for Health Canada said it is powerless to stop the sale of a product if its distributor does not claim any health benefits. It referred the Montreal Gazette to the Canadian Food Inspection Agency.

The CFIA said it merely enforces Health Canada directives.

Neither agency would comment on why apricot seeds are sold in Canada at all — as vitamins or snacks — given their known toxicity.

 

Upon arrival at Hôtel-Dieu Hospital, Brogan was given a tall Styrofoam cup of charcoal then placed on a gurney in the hallway to monitor his condition.

No one, from the person who answered the phone at poison control to the triage nurse to the doctor on duty, could believe that apricot seeds were being sold in Montreal.

Eight hours later, Brogan was released from hospital with a $1,125 bill. He had no health insurance, he explained.

“Those seeds were the most expensive snack I’ve ever eaten.”

Guetta went back to Rachelle-Béry to alert them of the danger. The store manager seemed alarmed and immediately took all the remaining packages off the shelves.

But when Guetta returned a few weeks later, there they were again. The superseed of the Hunza people.

 

 

 

 

 

November, 2017|Oral Cancer News|

The Unforgiving Math That Stops Epidemics

Author: Tara C. Smith
Source: www.quantamagazine.org
Date: October 26, 2017

As the annual flu season approaches, medical professionals are again encouraging people to get flu shots. Perhaps you are among those who rationalize skipping the shot on the grounds that “I never get the flu” or “if I get sick, I get sick” or “I’m healthy, so I’ll get over it.” What you might not realize is that these vaccination campaigns for flu and other diseases are about much more than your health. They’re about achieving a collective resistance to disease that goes beyond individual well-being — and that is governed by mathematical principles unforgiving of unwise individual choices.

When talking about vaccination and disease control, health authorities often invoke “herd immunity.” This term refers to the level of immunity in a population that’s needed to prevent an outbreak from happening. Low levels of herd immunity are often associated with epidemics, such as the measles outbreak in 2014-2015 that was traced to exposures at Disneyland in California. A study investigating cases from that outbreak demonstrated that measles vaccination rates in the exposed population may have been as low as 50 percent. This number was far below the threshold needed for herd immunity to measles, and it put the population at risk of disease.

The necessary level of immunity in the population isn’t the same for every disease. For measles, a very high level of immunity needs to be maintained to prevent its transmission because the measles virus is possibly the most contagious known organism. If people infected with measles enter a population with no existing immunity to it, they will on average each infect 12 to 18 others. Each of those infections will in turn cause 12 to 18 more, and so on until the number of individuals who are susceptible to the virus but haven’t caught it yet is down to almost zero. The number of people infected by each contagious individual is known as the “basic reproduction number” of a particular microbe (abbreviated R0), and it varies widely among germs. The calculated R0 of the West African Ebola outbreak was found to be around 2 in a 2014 publication, similar to the R0 computed for the 1918 influenza pandemic based on historical data.

Quantized Columns

If the Ebola virus’s R0 sounds surprisingly low to you, that’s probably because you have been misled by the often hysterical reporting about the disease. The reality is that the virus is highly infectious only in the late stages of the disease, when people are extremely ill with it. The ones most likely to be infected by an Ebola patient are caregivers, doctors, nurses and burial workers — because they are the ones most likely to be present when the patients are “hottest” and most likely to transmit the disease. The scenario of an infectious Ebola patient boarding an aircraft and passing on the disease to other passengers is extremely unlikely because an infectious patient would be too sick to fly. In fact, we know of cases of travelers who were incubating Ebola virus while flying, and they produced no secondary cases during those flights.

Note that the R0 isn’t related to how severe an infection is, but to how efficiently it spreads. Ebola killed about 40 percent of those infected in West Africa, while the 1918 influenza epidemic had a case-fatality rate of about 2.5 percent. In contrast, polio and smallpox historically spread to about 5 to 7 people each, which puts them in the same range as the modern-day HIV virus and pertussis (the bacterium that causes whooping cough).

Determining the R0 of a particular microbe is a matter of more than academic interest. If you know how many secondary cases to expect from each infected person, you can figure out the level of herd immunity needed in the population to keep the microbe from spreading. This is calculated by taking the reciprocal of R0 and subtracting it from 1. For measles, with an R0 of 12 to 18, you need somewhere between 92 percent (1 – 1/12) and 95 percent (1 – 1/18) of the population to have effective immunity to keep the virus from spreading. For flu, it’s much lower — only around 50 percent. And yet we rarely attain even that level of immunity with vaccination.

Once we understand the concept of R0, so much about patterns of infectious disease makes sense. It explains, for example, why there are childhood diseases — infections that people usually encounter when young, and against which they often acquire lifelong immunity after the infections resolve. These infections include measles, mumps, rubella and (prior to its eradication) smallpox — all of which periodically swept through urban populations in the centuries prior to vaccination, usually affecting children.

Do these viruses have some unusual affinity for children? Before vaccination, did they just go away after each outbreak and only return to cities at approximately five- to 10-year intervals? Not usually. After a large outbreak, viruses linger in the population, but the level of herd immunity is high because most susceptible individuals have been infected and (if they survived) developed immunity. Consequently, the viruses spread slowly: In practice, their R0 is just slightly above 1. This is known as the “effective reproduction number” — the rate at which the microbe is actually transmitted in a population that includes both susceptible and non-susceptible individuals (in other words, a population where some immunity already exists). Meanwhile, new susceptible children are born into the population. Within a few years, the population of young children who have never been exposed to the disease dilutes the herd immunity in the population to a level below what’s needed to keep outbreaks from occurring. The virus can then spread more rapidly, resulting in another epidemic.

An understanding of the basic reproduction number also explains why diseases spread so rapidly in new populations: Because those hosts lack any immunity to the infection, the microbe can achieve its maximum R0. This is why diseases from invading Europeans spread so rapidly and widely among indigenous populations in the Americas and Hawaii during their first encounters. Having never been exposed to these microbes before, the non-European populations had no immunity to slow their spread.

If we further understand what constellation of factors contributes to an infection’s R0, we can begin to develop interventions to interrupt the transmission. One aspect of the R0 is the average number and frequency of contacts that an infected individual has with others susceptible to the infection. Outbreaks happen more frequently in large urban areas because individuals living in crowded cities have more opportunities to spread the infection: They are simply in contact with more people and have a higher likelihood of encountering someone who lacks immunity. To break this chain of transmission during an epidemic, health authorities can use interventions such as isolation (keeping infected individuals away from others) or even quarantine (keeping individuals who have been exposed to infectious individuals — but are not yet sick themselves — away from others).

Other factors that can affect the R0 involve both the host and the microbe. When an infected person has contact with someone who is susceptible, what is the likelihood that the microbe will be transmitted? Frequently, hosts can reduce the probability of transmission through their behaviors: by covering coughs or sneezes for diseases transmitted through the air, by washing their contaminated hands frequently, and by using condoms to contain the spread of sexually transmitted diseases.

These behavioral changes are important, but we know they’re far from perfect and not particularly efficient in the overall scheme of things. Take hand-washing, for example. We’ve known of its importance in preventing the spread of disease for 150 years. Yet studies have shown that hand-washing compliance even by health care professionals is astoundingly low — less than half of doctors and nurses wash their hands when they’re supposed to while caring for patients. It’s exceedingly difficult to get people to change their behavior, which is why public health campaigns built around convincing people to behave differently can sometimes be less effective than vaccination campaigns.

How long a person can actively spread the infection is another factor in the R0. Most infections can be transmitted for only a few days or weeks. Adults with influenza can spread the virus for about a week, for example. Some microbes can linger in the body and be transmitted for months or years. HIV is most infectious in the early stages when concentrations of the virus in the blood are very high, but even after those levels subside, the virus can be transmitted to new partners for many years. Interventions such as drug treatments can decrease the transmissibility of some of these organisms.

The microbes’ properties are also important. While hosts can purposely protect themselves, microbes don’t choose their traits. But over time, evolution can shape them in a manner that increases their chances of transmission, such as by enabling measles to linger longer in the air and allowing smallpox to survive longer in the environment.

By bringing together all these variables (size and dynamics of the host population, levels of immunity in the population, presence of interventions, microbial properties, and more), we can map and predict the spread of infections in a population using mathematical models. Sometimes these models can overestimate the spread of infection, as was the case with the models for the Ebola outbreak in 2014. One model predicted up to 1.4 million cases of Ebola by January 2015; in reality, the outbreak ended in 2016 with only 28,616 cases. On the other hand, models used to predict the transmission of cholera during an outbreak in Yemen have been more accurate.

The difference between the two? By the time the Ebola model was published, interventions to help control the outbreak were already under way. Campaigns had begun to raise awareness of how the virus was transmitted, and international aid had arrived, bringing in money, personnel and supplies to contain the epidemic. These interventions decreased the Ebola virus R0 primarily by isolating the infected and instituting safe burial practices, which reduced the number of susceptible contacts each case had. Shipments of gowns, gloves and soap that health care workers could use to protect themselves while treating patients reduced the chance that the virus would be transmitted. Eventually, those changes meant that the effective R0 fell below 1 — and the epidemic ended. (Unfortunately, comparable levels of aid and interventions to stop cholera in Yemen have not been forthcoming.)

Catch-up vaccinations and the use of isolation and quarantine also likely helped to end the Disneyland measles epidemic, as well as a slightly earlier measles epidemic in Ohio. Knowing the factors that contribute to these outbreaks can aid us in stopping epidemics in their early stages. But to prevent them from happening in the first place, a population with a high level of immunity is, mathematically, our best bet for keeping disease at bay.

November, 2017|Oral Cancer News|

FDA Cracks Down on Marijuana Cancer Treatment Claims

Author: Anna Edney; Jennifer Kaplan
Source: www.bloomberg.com
Date: November 1, 2017

U.S. officials sent a warning to the marijuana industry, alerting online sellers they cannot market their products as a treatment for cancer.

The Food and Drug Administration sent letters to four companies on Tuesday, warning them about unsubstantiated claims that their marijuana-derived products can combat tumors and kill cancer cells. The firms sell products including oils and capsules made from cannabidiol, also known as CBD, a component of the marijuana plant that doesn’t cause the mind-altering effects of the other main component, tetrahydrocannabinol, or THC.

The agency told the companies they cannot make claims to treat or cure a disease when a product has never been studied as a treatment. Curbing the sale of CBD products with health claims could put a damper on the medical-marijuana market. Producers that are required to nix references to medical ailments may move toward the recreational side of the legal cannabis industry.

Eight states and Washington, D.C., have legalized pot for recreational use. Twenty-one additional states have legalized for medical purposes.

“We don’t let companies market products that deliberately prey on sick people with baseless claims that their substance can shrink or cure cancer and we’re not going to look the other way on enforcing these principles when it comes to marijuana-containing products,” FDA Commissioner Scott Gottlieb said in a statement.

The crackdown could also have a wider impact on the pharmaceutical industry. CBD is being researched in labs as potential treatment for certain diseases. Biotech company GW Pharmaceuticals Plc, for instance, is testing the component to treat certain forms of epilepsy.

Gottlieb hinted almost a month ago at a congressional hearing that the FDA may get tough on unproven marijuana claims. The companies that received warning letters are: Greenroads Health, Natural Alchemist, That’s Natural! and Stanley Brothers Social Enterprises. The companies have 15 working days to tell the FDA what corrective steps they will take.

Stanley Brothers runs the company CW Hemp, which said in an emailed statement it takes “regulatory compliance very seriously” and will work with the FDA to better monitor the information on its website. The other companies didn’t return requests for comment.

 

November, 2017|Oral Cancer News|

Understanding personal risk of oropharyngeal cancer: risk-groups for oncogenic oral HPV infection and oropharyngeal cancer

Author: G D’Souza, T S McNeel, C Fakhry
Date: October 19, 2017
Source: Academic.oup.com

Abstract

Background

Incidence of human papillomavirus (HPV)-related oropharyngeal cancer is increasing. There is interest in identifying healthy individuals most at risk for development of oropharyngeal cancer to inform screening strategies.

Patients and methods

All data are from 2009 to 2014, including 13 089 people ages 20–69 in the National Health and Nutrition Examination Survey (NHANES), oropharyngeal cancer cases from the Surveillance, Epidemiology, and End Results (SEER 18) registries (representing ∼28% of the US population), and oropharyngeal cancer mortality from National Center for Health Statistics (NCHS). Primary study outcomes are (i) prevalence of oncogenic HPV DNA in an oral rinse and gargle sample, and (ii) incident oropharyngeal squamous cell cancer.

Results

Oncogenic oral HPV DNA is detected in 3.5% of all adults age 20–69 years; however, the lifetime risk of oropharyngeal cancer is low (37 per 10 000). Among men 50–59 years old, 8.1% have an oncogenic oral HPV infection, 2.1% have an oral HPV16 infection, yet only 0.7% will ‘ever’ develop oropharyngeal cancer in their lifetime. Oncogenic oral HPV prevalence was higher in men than women, and increased with number of lifetime oral sexual partners and tobacco use. Men who currently smoked and had ≥5 lifetime oral sexual partners had ‘elevated risk’ (prevalence = 14.9%). Men with only one of these risk factors (i.e. either smoked and had 2–4 partners or did not smoke and had ≥5 partners) had ‘medium risk’ (7.3%). Regardless of what other risk factors participants had, oncogenic oral HPV prevalence was ‘low’ among those with only ≤1 lifetime oral sexual partner (women = 0.7% and men = 1.7%).

Conclusions

Screening based upon oncogenic oral HPV detection would be challenging. Most groups have low oncogenic oral HPV prevalence. In addition to the large numbers of individuals who would need to be screened to identify prevalent oncogenic oral HPV, the lifetime risk of developing oropharyngeal caner among those with infection remains low.

Introduction

Human papillomavirus (HPV) is the most commonly sexually transmitted infection in the United States. HPV now causes ∼70% of all oropharyngeal squamous cell cancer (OPC) in the United States [1] and the incidence of HPV-related OPC (HPV-OPC) among men has more than doubled over the past 20 years [2]. Indeed, OPC is projected to be more common than cervical cancer in the United States by 2020 [3]. Given the ‘epidemic’ of HPV-OPC, there is interest in identifying specific groups that could benefit from screening, if effective tests were developed.

Sexual behaviors responsible for exposure to oral HPV infection are common (80% of the US population reports ever performing oral sex) [4]. Given the ubiquitous exposure to HPV infection and resulting anxiety [5], there is interest in identifying healthy individuals most at risk for development of OPC. As oncogenic oral HPV infection is the precursor to malignancy, identification of individuals with oncogenic oral HPV infection may point to individuals with premalignant disease. Such risk triage could both inform screening approaches and assist the public in understanding personal risk. This analysis therefore aims to understand how common HPV16, oncogenic HPV and HPV-OPC are in groups of people with different risk factor profiles.

Methods

Study population

This study included 13 089 people ages 20–69 years old who participated in National Health and Nutrition Examination Survey (NHANES) between 2009 and 2014 and had oral HPV DNA testing. Analyses involving number of oral sex partners were limited to ages 20–59, with data for number of oral sex partners, resulting in a sample size of 9425. Incidence and incidence-based mortality data from SEER 18 registries between 2009 and 2014 [6] were used with NCHS mortality data for projections of OPC risk.

HPV measurement

As previously described [7, 8] oral HPV DNA was tested in exfoliated cells collected from an oral rinse and gargle sample using PCR amplification using PGMY 09/11 consensus primers and line blot for the detection of 37 specific HPV types. Oncogenic oral HPV was defined as detection of any of the following 12 types: HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59 [9].

Analytic methods

Analyses of NHANES oral HPV data were weighted by Mobile Examination Center (MEC) exam sampling weights, and conducted using SUDAAN software (release 11.0.1, Research Triangle Institute) to account for survey sample design. Projected OPC risk was calculated using DevCan software [10].

To better understand subgroup risk, prevalence of oncogenic HPV and HPV16 were explored stratifying by multiple factors including sex, sexual behavior, age, and current smoking. Groups with similar prevalence were combined to create parsimonious risk stratification of people with similar prevalence.

Results

Oncogenic oral HPV and oral HPV16 infection are rare in the general US population. As expected, prevalence of infection is higher among men than women of every age group (oncogenic HPV; 6.0% versus 1.1%, P < 0.001; Table 1). Prevalence of oncogenic oral HPV is contrasted with risk of OPC in Table 1 by sex and age groups. While oncogenic oral HPV is detected in 3.5% of all adults age 20–69, the lifetime risk of OPC is low (37 per 10 000). For example, among men 50–59 years old, 8.1% have an oncogenic oral HPV infection, 2.1% have an oral HPV16 infection, yet 0.7% will ‘ever’ develop OPC in their lifetime; and risk of developing OPC in the next 10 (0.2%) or 20 (0.4%) years is even lower (Table 1).

Table 1.

Oral HPV prevalence by sex and age, compared with the risk of developing oropharyngeal cancer (OPC) in each group

    Risk spectrum: infection to cancer

 

NHANESa (prevalence)

 

SEERb (OPC risk: cases/100 people) 

 

Sex  Age  Oncogenic Oral HPV (%)  Oral HPV16 (%)  Lifetime (%)  Next 20 years (%)  Next 10 years (%) 
Men
20–29 4.8 1.1 0.7 0.01 <0.01
30–39 4.7 1.5 0.7 0.07 0.01
40–49 6.2 2.3 0.7 0.3 0.06
50–59 8.1 2.1 0.7 0.4 0.2
60–69 6.1 2.4 0.5 0.4 0.3
Total 6.0 1.9 0.7
Women
20–29 1.4 0.3 0.2 <0.01 <0.01
30–39 1.0 0.3 0.2 0.01 <0.01
40–49 0.8 0.1 0.2 0.05 0.01
50–59 1.6 0.5 0.2 0.08 0.03
60–69 0.7 0.1 0.1 0.10 0.05
Total 1.1 0.3 0.2
Men and women All 3.5 1.1 0.4

a- Weighted prevalence accounting for NHANES study design weights to reflect the general US population.

b- Estimates of OPC risk combine data on cancer occurrence from SEER with population data. OPC is shown as risk per 100 people to contrast with HPV prevalence. For reference in interpretation, 0.6% risk represent that 0.6 people out of the 100 (or 6 out of 1000, or 600 out of 100 000) would develop OPC.

While prevalence of oncogenic oral HPV infection is low, the distribution of infections is not representative of the population (supplementary Table S1, available at Annals of Oncologyonline). Indeed 84% of oncogenic oral HPV infections in 20- to 69-year olds were among men. To elucidate why oncogenic oral HPV was more concentrated among certain groups, behavioral characteristics were considered. Performing oral sex and smoking are each strongly associated with detection of oncogenic oral HPV (Table 2) and HPV16 (supplementary Table S2, available at Annals of Oncology online). Oncogenic oral HPV prevalence is low (<2.5%) among both men and women who never performed oral sex. Prevalence of oncogenic oral HPV increased with number of lifetime oral sexual partners, up to 14.4% in men age 20–59 years old with ≥10 lifetime oral sexual partners (Table 2).

 

Table 2.

Oncogenic oral HPV prevalence by participant characteristics and behaviors

    Oncogenic oral HPV prevalencea(%)

 

 
Men  Women  All 
Characteristics (among those 20–69 years old)  No. of people  N = 6420  N = 6669  N = 13 089  P-valueb 
Sex
Women 6669 1.1 1.1 <0.0001
Men 6420 6.0 6.0
Currently smoke
No 10 041 4.5 0.9 2.6 <0.0001
Yes 3044 10.5 2.1 6.7
Age, in years
 20–29 2738 4.8 1.4 3.1 0.13
 30–39 2668 4.7 1.0 2.8
 40–49 2699 6.2 0.8 3.4
 50–59 2494 8.1 1.6 4.8
 60–69 2490 6.1 0.7 3.3
Race/ethnicity
 White non-Hispanic 5135 6.3 1.1 3.7 0.008
 Black non-Hispanic 2931 7.5 1.4 4.2
 Any race Hispanic 3347 4.5 1.3 2.9
 Other 1676 3.7 0.7 2.1
Ever oral sex (or man or woman)
 No 2453 2.3 0.2 1.1 <0.0001
 Yes 9272 6.5 1.4 4.0
Ever oral sex on a woman
 No 6660 3.6 1.0 1.4 <0.0001
 Yes 5095 6.4 3.5 6.2
Ever oral sex on a man
 No 7054 5.8 0.2 4.9 <0.0001
 Yes 4693 10.2 1.4 1.8
Number of partners performed oral sex on in lifetimec
 0 1661 2.4 0.2 1.2 <0.0001
 1 1877 1.2 1.0 1.1
 2–4 3165 4.8 0.7 2.5
 5–9 1363 3.9 2.5 3.3
 10+ 1359 14.4 3.0 11.1

a- Weighted prevalence accounting for NHANES study design weights to reflect the civilian non-institutionalized US population.

b-Wald F test (based on transforming the Wald χ2) for independence of row variable and oral HPV16, not accounting for sex (except where sex is the row variable).

C- Data on number of lifetime oral sex partners was not collected consistently in those 60 and older so is only presented among those 20–59 years old.

 

 

Oncogenic oral HPV prevalence was explored by sex, sexual behavior, and tobacco use to better understand groups that have higher and lower prevalence (Figure 1). Regardless of what other risk factors participants had, oncogenic oral HPV prevalence was low among those with only ≤1 lifetime oral sexual partner (women = 0.7% and men = 1.7%). Oncogenic oral HPV prevalence doubled among women with ≥2 versus 0–1 lifetime oral sexual partners (1.5% versus 0.7%, P = 0.02), but remained low among women with higher number lifetime oral sexual partners (Table 2). Oncogenic oral HPV prevalence was highest among men who currently smoked and had ≥5 lifetime oral sexual partners (14.9%, 95% CI = 11.4–19.1). Men with only one of these risk factors (i.e. either smoked and had two to four partners or did not smoke and had ≥5 partners) had ‘medium risk’, with 7.3% (95% CI = 5.8–9.1) oncogenic oral HPV prevalence (Figure 1). Findings were similar when considering oral HPV16 infection specifically.

 

What is my risk of oral HPV? Prevalence of oral HPV16 and any oncogenic oral HPV infection by risk group. In the ‘very low-risk’ group (among women with 0–1 lifetime oral sexual partners), oncogenic oral HPV was similar among smokers and nonsmokers (1.8% versus 0.5%, P = 0.26). In the ‘low-risk’ group of women, oncogenic oral HPV prevalence was 1.5% among women with two or more lifetime oral sexual partners. In the ‘low-risk’ group of men, oncogenic oral HPV prevalence was 1.7% among men with 0–1 lifetime oral sexual partners and was higher among men who did not smoke and had 2–4 lifetime oral sexual partners (4.1%, P = 0.0042). In the ‘medium risk’ group, oral HPV16 prevalence was 7.1% among men who smoke and had 2–4 partners and 7.4% among men who do not smoke and had 5+ partners (P = 0.87).

 

Discussion

This analysis highlights that the yield of oncologic oral HPV screening would be limited in most groups in the United States. With the increasing incidence of OPC, there is a need to understand how to identify individuals at risk of OPC. Oncogenic oral HPV detection is attractive as it samples the relevant epithelium in a non-invasive method, has relatively low cost and serves as a biomarker for HPV-OPC. However, for screening to succeed, a high prevalence population is needed to limit false positives, and balance the psychologic and physical harms of screening with the benefits.

From this analysis, it is clear that screening based upon oncogenic oral HPV detection would be challenging. Women across all categories have low prevalence of infection and low risk of OPC and therefore benefits of screening are unlikely to outweigh harms in this group. The higher prevalence of oncogenic oral HPV in men than women is thought be due to both a higher per partner risk of acquisition when performing oral sex [11, 12], and decreased clearance among men than women [11, 13]. While there are specific risk groups of men enriched for oncogenic oral HPV, most men have low prevalence of infection. Even among the elevated risk group, the majority of men do not have a prevalent oncogenic oral HPV. In addition to the large numbers of individuals who would need to be screened to identify prevalent oncogenic oral HPV, the lifetime risk of developing OPC among those with infection remains low [11, 14].

These characteristics suggest that other tests will need to be combined or supplant present methods to accurately identify those with the greatest risk of OPC in the population. Serum HPV oncoprotein antibody tests are specific [15], but are even rarer than oral HPV16 infection [16], so may be impractical to use in most groups. An additional challenge for screening is that precursor lesions for HPV-OPC have not been found and the ability to detect lesions early in an ‘elevated-risk’ group is unknown.

With growing appreciation of the relationship between oral sex, infection, and cancer, some individuals have questions about their risk of having oncogenic oral HPV infection. To address concerns about infection among individuals with high number of oral sex partners or others concerned about their cancer risk, the infographic can be used to reassure that oncogenic oral HPV prevalence is low among most groups. This analysis has several imitations. Data on oral HPV infection were cross-sectional, with no information linking HPV and SEER data used for cancer risk. Comparing oncogenic oral HPV prevalence and OPC risk in this way informs potential future screening studies, and personal risk assessment. In summary, this analysis shows that screening based upon oncogenic oral HPV infection will not be useful and presents data to communicate to the layperson the low risk of infection and cancer.

Acknowledgements

The authors acknowledge Maura Gillison who led the testing for oral HPV in NHANES provided in the publicly available dataset. This dataset has provided investigators the opportunity to better understand the epidemiology of oral HPV infection in the United States. We also acknowledge the contributions of the Oral Cancer Foundation.

Funding

National Institute of Dental and Craniofacial Research (NIDCR) (R35 DE026631).

Disclosure

The authors have declared no conflicts of interest.

 

References

1 Saraiya M, Unger ER, Thompson TD et al. US assessment of HPV types in cancers: implications for current and 9-calent HPV vaccines. J Natl Cancer Inst 2015; 107(6): djv086

 

2 Jemel A, Simard EP, Dorell C et al. Annual Report to the Nation on the Status of Cancer, 1975-2009, featuring the burden and trends in human papillomavirus(HPV)-associated cancers and HPV vaccination coverage levels. J Natl Cancer Inst 2013; 105(3): 175-201.

 

3 Chaturvedi AK, Engels EA, Pfeiffer RM et al. Human papillomavirus and rising oropharyngeal cancer incidence in the United States. J Clin Oncol 2011;29(32): 4294-4301

 

4 D’Souza G, Cullen K, Bowie J et al. Differnece in oral sexual behaviors by gender, age, and race explain observed difference in prevalence or oral human papillomavirus infection. PLoS One 2014; 9(1): e86023

 

5 D’Souza G, Zhang Y, Merritt S et al. Patient experience and anxiety during and after treatment for and HPV-related oropharyngeal cancer. Oral Oncol 2016; 60: 90-95.

 

6 SEER Incidence and Incidence-Based Mortality Date, SEER 18 Regs (Excl Lousiana) 1973-2014; http://seer.cancer.gov/date/ (8 May 2017, date last accessed).

 

7 Gillison ML, Broutain T, Pickard RKL et al. Prevalence of oral HPV infection in the United States, 2009-2010. JAMA 2012;307(7): 693-703.

 

8 NHANES 2013-2014: Human Papillomavirus (HPV)- Oral Rinse Data Documentation, Codebook, and Frequencies:

https://wwwn.cdc.gov/Nchs/Nhanes/2013-2014/ORHPV_H.htm (2 May 2017, date last accessed).

 

9 IARC. Human Papillomavirus; http://monographs.iarc.fr/ENG/Monographs/vol100B/mono100B-11.pdf (23 May 2017, date last accessed)

 

10 Devcan: Probability of Developing or Dying of Cancer- Surveillance Research Program; https://surveillance.cancer.gov/devcan/ (8 May 2017, date last accessed).

 

11 D’Souza G, Wentz A, Kluz N et al.   Sex differnces in risk factors and natural history of oral human papillomavirus (HPV) infection. J Infect Dis 2016;213(12):1893-1896.

 

12 Chaturvedi AK, Graubard Bl, Broutian T et al. NHANES 2009-2012 findings: association of sexual behaviors with higher prevalence of oral oncogenic human papillomavirus infections in U.S. men. Cancer Res 2015; 75(12): 2468-2477.

 

13 Beachler DC, Sugar EA, Margolick JB et al. Risk Factors acquisition and clearance or oral human papillomavisur infection among HIV-infected and HIV-uninfected adults. Am J Epidemiol 2015; 181(1): 40-53.

 

14 Pierce Campbell CM, Kreimer AR, Lin H-Y et al. Long-term persistence of oral human papillomavirus type 16: the HPV infection in men (HIM) Study. Cancer Pres Res Phila Pa 2015; 8(3): 190-196.

 

15 Holzinger D, Wichmann G, Baboci L et al. Sensitivity and specificity of antibodies against HPV16 E6 and other early proteins for the detection of HPV16-driven oropharyngeal squamous cell carcinoma. Int J Cancer 2017; 140(12):2748-2757.

 

16 Beachler DC, Waterboer T, Pierce Campbell CM et al. HPV16 E6 seropositivity among cancer-free men with oral, anal or genital HPV16 infection. Papillomavirus res 2016; 2: 141-144.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

October, 2017|Oral Cancer News|

3 Lessons From An Alarming Case Of Mistaken Cancer Gene Test Results And Surgery

Date: October 28, 2017
Source: Forbes.com
Author: Elaine Schattner

A horrifying story broke last week about a 36-year-old Oregon woman who had elective surgery to remove her uterus and breasts. Elisha Cooke-Moore underwent a prophylactic total hysterectomy and bilateral mastectomy, with nipple-sparing reconstruction and implants, after medical practitioners informed her she had cancer-causing genes. Only later, she learned she didn’t have the abnormality about which she’d been informed. There’s a lawsuit.

As reported in The Washington Post, Cooke-Moore expressed concerns to a doctor about her family’s cancer history before getting tested for mutations in BRCA-1, BRCA-2 and related genes in 2015. A nurse practitioner reviewed the results and erroneously told her she had Lynch syndrome because of an MLH1 mutation. BRCA testing was “negative.” It’s not clear if any doctor directly reviewed the lab report. An obstetrician-gynecologist informed Cooke-Moore that her chances of developing breast cancer were 50% and for uterine cancer up to 80%. In 2016, at least two surgeons operated.

Cooke-Moore discovered the mistake while looking over her medical records: The MLH1 result was “negative,” she noted in 2017. “I am damaged for the rest of my life,” Cooke-Moore told The Washington Post.

Never mind the specifics. While it sounds like the plaintiff received egregious care, and I am sympathetic, I see this as a larger story of confusion over genetic test results leading to irreversible harm. My aim here is not to probe Cooke-Moore’s results or the circumstances of her decisions, but to consider the lessons for other patients and doctors. This case should be a wake-up call about the quality of DNA testing and what variable guidance patients receive about their results. The implications are broad.

Checking genes for presence or absence of mutations is not straightforward as you might think. Mutations vary: They’re rarely “positive” or “negative,” end of story. Some doctors may not fully appreciate the nuances of genetic findings. While some DNA abnormalities are clearly linked to disease, such as mutations tied to cystic fibrosis or sickling of hemoglobin, often there’s a range of severity of illness and pathology among affected patients. Among the cancer risk genes, BRCA-1 and -2 are probably the best studied. Yet even for those, doctors don’t yet understand why some people who inherit BRCA mutations don’t develop cancer, i.e., what mitigates disease risk. Some changes are deemed variants of uncertain significance.

Given the enormity of this subject, I’ll focus on three practical measures to reduce regrettable outcomes after testing for cancer genetic risk.

  1. If you consider getting tested for familial cancer risk, ask where your sample will be evaluated, and exactly what genes will be tested.

The practitioner may or may not know the answer to these questions. But part of the point of asking is to ensure that the responsible physician or genetics counselor is clued in to the details because gene testing companies vary in their methods, which gene variants they report, how fully they report on those, and how they interpret any detected abnormalities.

Some companies, like Myriad Genetics, focus on BRCA and related cancer risk-associated genes. Myriad offer various testing panels to assess hereditary cancer risk. Some large and more general commercial laboratories, like LabCorp and Quest Diagnostics, offer BRCA-related panels (BRCAssure and BRCAdvantage, respectively). Ambry is another player in this field. More recently Color Genomics, a San-Francisco based company, entered the fray; they’ll check your BRCA status for less. Some universities and hospitals offer “in house” testing.

These labs (and this is not a comprehensive list) use distinct and sometimes proprietary ways of extracting DNA from samples, amplifying and analyzing genetic material. They employ different scientists who develop methods and interpret results variously in context of the rapidly-growing literature on cancer risk and cancer-related mutations. The doctor who orders genetic tests should be aware of these possible differences.

At the minimum, before making any decisions I’d want to know that my test was performed in a CLIA-certified laboratory.

  1. Before taking any treatment based on a genetic test result, hit the pause button. Get a copy of the full report and keep it. Ask questions. Try to get a second opinion.

Before agreeing to anything so drastic as prophylactic surgery, or taking medication aimed at reducing cancer risk, you might want to have the test repeated, to confirm or supplement initial results. Even nonprescriptive changes, like adjusting your diet, or participating in a clinical trial for people with specific genetic variants, carries possible benefits and risks. You might wind up taking a medicine, or getting screened in a way that you would not have otherwise.

Among the questions I’d want to ask a doctor are these: “How confident are you about the accuracy of my test result?” and “What are the implications for my health?”

Whenever possible, get a second opinion before a major procedure or treatment is implemented. Ideally, advice would come by a physician familiar with both the nitty-gritty of DNA testing and the relevant medical condition. Keep in mind, experts may have informed but distinct and biased perspectives on the significance of an abnormality, such as an MLH1 mutation. The most knowledgeable physicians may not have ready answers when it comes to interpreting DNA findings in context of an individual patient with a unique medical history and concerns. Consulting with a genetics counselor may also be helpful.*

  1. Use the web and other resources, including patient-oriented organizations, to learn what you can about your genetic results.Here’s a partial list of societies and websites that provide information about genetic testing for cancer risk:

Cancer.net offers information about hereditary cancer syndromes that is provided by the American Society of Clinical Oncology;

FORCE (Facing Our Risk of Cancer Empowered) is a patient-oriented organization with many resources and detailed information for people affected by a familial disposition to developing breast, ovarian and other cancers;

The National Cancer Institute’s Genetics of Cancer page includes numerous links to NIH resources for particular cancer risk genes and syndromes;

National Society of Genetic Counselors details the role of genetic counselors and refers to several resources for patients;

The American Society for Human Genetics is a professional organization that offers general information on gene testing and links to additional resources.

I’m constantly amazed at the explosive field of diagnostic human genetic testing. Despite my concerns about the quality and guidance of interpreting results, I’m impressed by the power of diagnostic human genetic testing. For people who are ill, gene testing can be enormously helpful in establishing the cause of disease, pinpointing a diagnosis, and in some situations knowing how best to treat a medical condition. For those who have reason to worry about inheriting a disposition to disease, gene testing could offer life-saving information about pre-emptive or risk-reducing interventions. In each of these circumstances, informed guidance provided by doctors — in interpreting results and in clinical decision-making — is crucial.

 

October, 2017|Oral Cancer News|