Patent Application
20200324135
This patent application is for a device and method for treating eight kinds of cancer using ultraviolet radiation. For at least eight cancers, there is the same geographic pattern—north. The more north we travel, the more people die.
This insight came when writing the last two chapters of a “big data” project on US cancer death rates. I hope to publish the longer work as a book called “Cancer in America: The Risk of Living North” by Keith Reed Greenbaum. While I refer to this document here as “the book”, I decided not to incorporate it as part of the patent application believing that the information I present is sufficient to stand on its own.
What explains this north pattern of dying from cancer? While I raise two possibilities in the book, I believe the strongest one is a change in sunlight as we go north. As we move away from the equator, sunlight reaches the ground more on an angle which makes it less intense. This includes the ultraviolet portion of sunlight which weakens. In models for eight kinds of cancer, I show a statistical connection between the diminished intensity of ultraviolet reaching the ground (in the largest city of the state) and an increase in deaths from cancer in that state as we move north.
If the intensity of ultraviolet can account for a substantial portion of the differences in the number of people dying from various cancers from one state to the next, then perhaps dying from cancer might be due in part to a lack of exposure to ultraviolet that is intense enough. This possibility constitutes the evidence for the device and method below for treating certain cancers. Turning this connection around the other way, perhaps the artificial exposure to ultraviolet of the necessary intensity might be an effective treatment for cancer.
How am I the first to uncover this connection between the diminished intensity of ultraviolet and dying from cancer? I had the good fortune to make contact with an expert at NOAA who works on the UV Index, a daily prediction of the intensity of ultraviolet reaching the ground in major US cities. At my request, he changed the UV numbers from daily to yearly form. This is what worked for revealing this connection between ultraviolet and cancer. The direction, however, turned out to be in the opposite direction than expected. If more people died from cancer the weaker ultraviolet became, then maybe ultraviolet might work as a treatment for cancer.
As I stated above, this possible connection between ultraviolet and cancer is the result of a “big data” project which includes virtually every person who died of a given cancer in the United States over the course of a three-year period. I intend to construct the machines based on the Hawaii sun, the place that the statistical result identifies as having the most intense ultraviolet over the course of the year in the United States, which is, in turn, linked to the fewest cancer deaths, generally speaking. The actual measurements will be modified to fit even more closely with my interpretation of the statistical result.
In sum, variations in death rates from cancer might be connected with a specific portion of naturally occurring sunlight that is not strong enough. This new knowledge provides a powerful foundation for a novel treatment which has a reasonable chance of working. The goal is to significantly increase the lifespan of those dying from these cancers.
As a final part of this introductory section, I chose eight cancer death categories which should fall under the purview of this patent. While this northern pattern of cancer deaths applies to deaths from most kinds of cancers, for these eight kinds, I was able to construct individual models which show both a northern pattern as well as the possibility that this pattern is the result of a connection with variations in the intensity of ultraviolet. I designate the following as the eight northern cancers: lung, melanoma, ovarian, urinary (including bladder), uterine, Non-Hodgkin's lymphoma, adult leukemia and prostate.
Because these are death categories, they include the extra auxiliary locations of cancers in that category. I specify such locations for two of the cancers as follows. The lung category includes “[m]alignant neoplasms of trachea, bronchus and lung”. Urinary tract cancer includes bladder cancer (some 54 percent) as well as cancers of the kidney, ureter and urethra.
Based on my calculations, the above cancers constitute close to half of all cancer deaths in the United States, some 49 percent (of the six hundred thousand and fifteen thousand expected to die during the year 2017, according to the American Cancer Society). This new device and method, then, has the potential to prolong the lives of around three hundred thousand people dying from cancer every year.
The key feature of the device is the intensity of ultraviolet which comes from the statistical result showing a link between stronger ultraviolet and fewer cancer deaths in the United States. This would be set to mimic the yearly average for ultraviolet intensity in the place with the strongest sun—Honolulu Hi. Based on measures of the yearly UVI (UV Index) for American cities, over a total of ten years (one plus nine) and modified by actual sun measurements on location, this proposed setting would maximize the chances for creating a cancer treatment that is both safe and effective.
The radiation would be almost entirely in the ultraviolet range. It would begin at the beginning of the higher energy UVB portion at a value of 280 nanometers. It would continue up through the end of the UV range ending with the weakest wavelength of the UVA range at 400 nanometers.
The key attribute of ultraviolet intensity is the B portion as measured by a Solarmeter Model 6.0 Standard UVB Meter (after milliwatts per square centimeter is converted to watts per square meter) which would be set at 3 watts per square meter. The B portion is foremost because the UV Index itself is a weighted measure which augments the role of the stronger B portion to focus on the effect of sunlight on human skin. This setting is based on an average of actual summer and winter measurements in Hawaii (near Waikiki Beach in Honolulu), this average itself being an attempt to mimic the year-round strength of ultraviolet in this version of the UV Index used in the research. This setting would maximize the chances of creating a cancer treatment that, while effective, might also be safer because the strength comes from a range that is an average of naturally occurring intensity values. The UV Index value would be between the lower actual measured average value of 6.6 and the UV Index value of 10, toward the high in the statistical research.
As the goal would be the minimum exposure necessary to achieve a therapeutic result, the device would include three sizes with the smallest effective version to be preferred. The two smaller versions would make shipping easier. The first would be a facial-style tanner with dimensions 22 inches wide, 9 inches deep and 14 inches tall. The Medium machine would have dimensions of about 2 feet tall and 1 foot wide. Both smaller machines would have four florescent-style tubes created with the ultraviolet specifications mentioned above. The large machine would be one row of five or six foot long florescent-style tubes preferably in a frame that can be tilted for use standing or lying. There would be a minimum of six such tubes in the row.
For all three size machines, the distance from the patient would be determined by the value of UVB to be set at 3 watts per square meter. The Small unit would be employed on the face but might also be employed in other areas related to the location of the cancer. The same is true for the Medium unit. For the Large machine, the patient would need to be undressed but covering the eyes with UV protective goggles, necessary as well for the two smaller machines.
While treatment time would be determined experimentally, the beginning goal would be 20 minutes per day three times a week. For the Large, full body version of the device, this would mean 10 minutes on the front and 10 minutes on the back. The time of a session would be worked up to this maximum gradually to prevent skin burning.
The first distinctive feature of these machines and this method is the purpose. This is probably the first ultraviolet-based device and method designed specifically for treating various cancers.
Second is its exclusive focus on only one of the three portions of sunlight. While the energy from sunlight is typically divided (from highest energy) into ultraviolet, visible light and infrared (heat), this device and method is careful to employ only one of the three portions—ultraviolet. Great care will be exercised to ensure that no energy from the infrared portion is included. As for visible light, this too would be excluded with the exception of a small portion to make sure that the human eye can discern when the unit is on.
Third, it is the only device specifically designed to mimic the intensity of ultraviolet in the major American city with the highest yearly value. Of course, the purpose here is to imitate conditions based on the statistical connection between the intensity of ultraviolet reaching the ground in that place over the year and fewest deaths from cancer of various types.
For the eight premiere northern cancers, there are two grouping. In the first group of five—lung, melanoma, ovarian, urinary and uterine, the individual models point to diminished ultraviolet in sunlight as we travel north as the strongest explanation. In the second grouping, including lymphoma, leukemia and prostate, the strongest result in the book pointed to a different environmental factor that varies as we travel north—the Earth's stronger magnetic field.
Based on the hunch that this same northern pattern might be the result of one rather than two environmental factors, I reworked this second group to fit the possibility that these too are linked with the diminished strength of “sunlight”. In the final two chapters of the book, I did this by creating new models after the three cancers were added together. Here for this application, I went further by redoing the final individual models to see if I could replace Earth magnetism with ultraviolet. This was extremely easy to do for lymphoma and adult leukemia.
For prostate, the exercise yielded a weaker result with a statistical significance value of 0.009, under 0.01, my cut-off, surely better than the standard 0.05 cut-off, but still, not as strong as the other results in terms of reliability. I decided to include prostate here because the thrust of the evidence—considering both individual models as well as the aggregated models at the end of the book—led me to believe that prostate is also a northern cancer. For this reason, it deserves to be with this group of the eight northern cancers and I believe that there is a reasonable chance that the above treatment might work for this cancer as well.
Now I present more detail about the evidence which suggests a link between deaths from these various northern cancers and diminished ultraviolet in sunlight. I start with the yearly death rates for each cancer by state for a given set of relatively recent years. This includes all of the deaths from a given cancer during the time period as best as we were able to record. I believe that all of these death rate lists were from the CDC web site (The Center for Disease Control) using a table called Health Data Interactive, a project that close in July, 2016. Using a data set of state-level items I developed over a twenty-year period, most from public sources, I tested many items in a multiple regression model to see what might be linked with the pattern of deaths from that cancer. In the final model, I showed a link between one environmental item that varies in a northern pattern and dying from that cancer.
Lastly, using the regression equation, I created a new “predicted” death rate list for the cancer by holding constant the less interesting items (by inserting their mean value in the equation) and letting vary only the northern item. In this new death rate list, the difference between the state with the highest death rate and the one with the lowest death rate was the size decrease in deaths that was due exclusively to this environmental item that changed as we moved from south to north. For the version in this application, all of these new death rate constructions vary only ultraviolet based on the yearly intensity of ultraviolet in the largest city of the state.
I soon present these percent decreases in death rates as one way to represent the power of the finding, the possibility that deaths from each cancer might have dropped substantially if ultraviolet had been stronger in intensity. This provides the evidence for the size of this possible connection and the foundation for the new treatment for cancer implicit in this device.
For all eight cancer death models, I show a link between ultraviolet and death rates using one of two versions of the UV Index, the first from 1996 in Table 12-3 and the second from 2006-2014 in Table 7-3, (the out of order table numbers being from the book). (“District” means Washington D.C.).
Both show the least intense ultraviolet in Alaska (Anchorage) and the most intense in Hawaii (Honolulu). I present these results suggesting that the death rate in Alaska could have been this percent lower had it had the same intensity of ultraviolet in sunlight that Hawaii had. These numbers for the eight northern cancers follow below in a little more detail.
The Eight Northern Cancers and their Link to the Insufficient Intensity of Ultraviolet
I will start with lung which happens to be the biggest cancer in terms of the number of people who die from it, (some 27 percent of the total). Table 3-1 is the yearly death rate from lung cancer by state during the years 2011 and 2013.
The lung cancer model is in Table 3-4 consisting of two items: the percent who have attended some college (fewer deaths) and the UVI value (UV index score for the largest city of the state between 2006 and 2014). The higher the ultraviolet, the fewer the lung cancer deaths.
Holding constant the huge effect of college results in the new predicted death rate for lung cancer which shows the effect of ultraviolet.
This predicted death rate list appears in Table 3-5 showing the fewest deaths in Hawaii, 55.2 per hundred thousand people, and the most in Alaska with 74.8.
Using the highest death rate as the base: 74.8/1=55.2/x. 55.2=74.8x. x=55.2/74.8=0.738. With the highest level of ultraviolet, the death rate is only some 74 percent of the original size. 1−0.73796=0.26. Due to ultraviolet, the death rate from lung cancer in the place with the highest ultraviolet is 0.262 lower, or about 26 percent lower.
Next is melanoma. Table 6-1 shows the death rate by state between 2008 and 2010.
The melanoma model appears in Table 6-5 with three items. Having a dog, more deaths, older age (65 or older), more deaths, and ultraviolet in 1996, fewer deaths.
Table 6-6 shows the new predicted death rate holding constant dog and older age to see the size of the effect of ultraviolet on death rates from melanoma.
In Hawaii, there are 2.67 deaths and in Alaska, 4.66 deaths (per hundred thousand). 4.66/1=2.67/x. 4.66x=2.67. x=2.67/4.66. x=0.57296. In the place with the highest ultraviolet, deaths from melanoma are only about 57 percent the size. 1−0.57296=0.427. This is a predicted death rate from melanoma that is 42.7 percent lower or about 43 percent lower.
Next is dying from ovarian cancer. Table 12-1 shows the state death rate from ovarian cancer in 2004-2006 (with the exception of Alaska being between the years 2003-2005).
The ovarian model is in Table 12-4 consisting of two items: older age (more deaths) and ultraviolet in 1996 (stronger, fewer deaths).
The predicted death rate list is in Table 12-5.
Holding older age constant, we can now see the size of the effect of ultraviolet on these death rates. In Hawaii, this is 5.03 deaths and in Alaska, it is 8.99 deaths. 8.99/1=5.03/x. 8.99x=5.03. x=5.0318.99. x=0.5595. Death rates from ovarian cancer are only about 56 percent the size in the state with the highest ultraviolet (compared with the lowest). 1−0.5595=0.4405. Due to ultraviolet, these predicted death rates from ovarian cancer are about 44 percent lower.
Next is urinary tract cancer, a death category the majority of which is bladder cancer. The yearly death rate from urinary tract cancer by state is in Table 7-1 for the years 2004 and 2006.
The model for urinary tract cancer appears in Table 7-4 and consists of two items.
More people in a state who are in the age 65 and over category, more deaths. The second item is the intensity of ultraviolet reaching the ground over the course of the year in the largest city of the state. This is for the years 2006 to 2014. The stronger the ultraviolet, the fewer the deaths from cancers of the urinary tract.
The reworked predicted death rates appear in Table 7-5.
Older age is held constant so we can see the size of the effect of ultraviolet by itself on these death rates. In Hawaii, this urinary tract death rate is 6.1 deaths per hundred thousand people. In Alaska, it is 10.9 deaths. 10.9/1=6.1/x. 10.9x=6.1. x=6.1/10.9. x=0.5596. Due to stronger ultraviolet, the death rate from urinary tract cancer is only 0.5596 or about 56 percent the size. 1−0.55963=0.44037. This predicted death rate from urinary tract cancer is 44 percent lower due to stronger ultraviolet.
Next is uterine cancer. The death rate for uterine cancer by state can be found in Table 13-1 for the years 2012-2014.
The model for uterine is in Table 13-5.
It has three items. Older age, more deaths. Particle air pollution in the metropolitan area of the largest city of the state, more deaths. Lastly is ultraviolet, the yearly average for 1996 in the largest city. The more intense this ultraviolet reaching the ground, the fewer the deaths from uterine cancer (for the size of the population).
In the book, I chose in Table 13-6 (not shown) to hold constant only one of the two items so the predicted rate there does not give us what we need right now—the specific effect of ultraviolet on these death rates. For this reason, I redid the exercise for this purpose in a supplemental table I will call Table 13-6-2.
In this recalculation, the predicted death rate in Alaska is 4.40 deaths while in Hawaii, it is only 2.67 deaths. 4.40/1=2.67/x. 4.40x=2.67. x=2.6714.40. x=0.6068. Due to ultraviolet, the death rate is only about 61 percent the size in Hawaii compared with Alaska. 1−0.6068=0.3932. The death rate from uterine cancer, due to stronger ultraviolet, is lower by 39.32 percent or by around 39 percent.
Now we are at the second group of three cancers including lymphoma, adult leukemia and prostate. In the book, I used models suggesting a different environmental factor which varies as we drive north might be responsible for this pattern of more deaths. For the purpose here, I rather easily took each of the three models and replaced this item (geomagnetism) with ultraviolet. From the new models that resulted, I used the equation to create a new predicted death rate list for each cancer so we could see the size of the effect of ultraviolet in shrinking these death rates as well.
To repeat the rationale, the exercise is based on the reasonable possibility that only one environmental factor might be responsible for the northern pattern and that it might, in the end, be the difference in the intensity of sunlight between places. Of course, the ultraviolet portion of sunlight gets weaker as we go north in the United States.
The first cancer in this group is Non-Hodgkin's lymphoma. The starting death rate is unchanged and can be found in Table 8-1 for the years 2004-2006.
Using the book model in Table 8-4 (not shown), I will now replace the environmental item with ultraviolet in Table 8-4-2.
aPredictors: (Constant), UVI0614, ACE65IN6
aDependent Variable: LYMPH46
The adjusted R Square is 0.824, slightly below the 0.837 of the original model. It includes the more recent ultraviolet measure for the years 2006-2014.
Using the equation in this model, I hold constant the age effect to see the size of the ultraviolet one which is the only thing to vary. According to this predicted list of death rates from lymphoma in Table 8-5-2,
The highest is for Alaska with 8.04 deaths per hundred thousand. The lowest is Hawaii with 5.45 deaths. 8.04/1=5.45/x. 5.45=8.04x. x=5.45/8.04. x=0.67786. Based on the difference in ultraviolet alone, the death rate from lymphoma in the lowest death rate state of Hawaii is only 0.67786 or about 68 percent the size. 1−0.67786=0.32214. Due to stronger ultraviolet, the predicted death rate from lymphoma declines by 32.2 percent or by close to a third.
Second now in this group of three cancers is leukemia. This does not include deaths among children as all the analyses are for people age 18 and older. We start with the death rates for this cancer between the years 2011-2013 in Table 10-1.
Using the leukemia model in Table 10-5 (not shown), we rework it replacing magnetism with ultraviolet in Table 10-5-2.
aPredictors: (Constant), IVI0614, AGE65IN6, DOGHOUSE
aDependent Variable: LEUK1113
To my surprise, the Adjusted R Square comes out the same as the original model, 0.752 (something I was surely not aware of at the time I was writing the book).
Using the equation in this ultraviolet model, I hold constant both older age (more deaths) and having a dog (more deaths) to see the specific effect of ultraviolet (more ultraviolet, fewer deaths) in Table 10-6-2.
The ultraviolet item that works best here is for the nine years between 2006 and 2014. The predicted death rate from leukemia is highest in Alaska at 10.89 deaths and lowest in Hawaii at 7.32 deaths. This difference can be accounted for entirely due to the effect of ultraviolet on these death rates, based on this model. 10.89/1=7.32/x. 10.89x=7.32. x=7.32/10.89. x=0.67218. Due to stronger ultraviolet, the predicted death rate in Hawaii from leukemia is only some two thirds the size that it is in the state with the highest death rate (some 67 percent). 1−0.67218=0.328. This means that the death rate from adult leukemia is reduced by 32.8 percent, almost 33 percent or by almost a third.
Lastly now is prostate cancer. Again here, we begin with the actual death rate list for prostate cancer deaths between 2010 and 2012 which can be found in Table 11-1.
Taking the prostate model from the book in Table 11-4 (not shown), we change geomagnetism to our relevant item that varies as we go north, ultraviolet, in the new model in Table 11-4-2.
aPredictors: (Constant), ULTRA96, ACE65IN6
aDependent Variable: PROS1012
In this original model, the Adjusted R Square is 0.583. In this replacement model, the Adjusted R Square is 0.510, not as high. As mentioned, the statistical significance is 0.009, not as good as other models but still, below the 0.01 limit I use and well below the 0.05 limit that is more common.
Holding constant the effect of older age now, we can see the size of the intensity of ultraviolet on prostate cancer death rates in Table 11-5-2.
In this model, ultraviolet in 1996 worked best. For prostate cancer, the predicted death rate goes from a high of 13.11 deaths in Alaska to a low of 10.59 deaths in Hawaii. 13.11/1=10.59/x. 13.11x=10.59. x=10.59/13.11. x=0.80778. Due to difference in the intensity of ultraviolet, the death rate from prostate cancer in the place with the strongest “sun” is only some 80.8 percent. 1−0.80778=0.192. This is a death rate that is 19.2 percent lower.
While these numbers are difficult to translate into how effective an ultraviolet-based device might be for treating these eight northern cancers, they probably give us some indication of the effectiveness that might be expected.
We can now summarize the results in size order based on this percent decrease from the state with the lowest intensity of ultraviolet, Alaska, to the one with the highest level, Hawaii. Here is the percent decrease in death rates for the eight northern cancers in size order that can be attributed specifically to the difference in the intensity of ultraviolet in sunlight reaching the ground over the course of the year. The more intense the sunlight, the fewer the deaths.
1. ovarian—44.1 percent lower
2. urinary (including bladder)—44.0 percent lower
3. melanoma—41.7 percent lower
4. uterine—39.3 percent lower
5. leukemia (adult)—32.8 percent lower
6. lymphoma (Non-Hodgkin's)—32.2 percent lower
7. lung—26.1 percent lower
8. prostate—19.2 percent lower
Email: keithmeister@hotmail.com
