Implementation of New Technology
Posted by ron in Commissioning, Medical Physics, Misc, Quality Assurance, Radiation Oncology, Training, Treatment Planning on April 13, 2012
Hello again.
This is going to be a bit different, because it doesn’t directly relate to current research or news items. This is just a pet peeve of mine, and something I think needs to be said about the acquisition of any new technology.
In my work I have travelled to literally hundreds of departments around the country over the last 20 years, usually training the center in new technologies. (In roughly chronological order, IMRT, IGRT, gating/motion management, radiosurgery, SBRT- haven’t gotten to protons yet). There are of course a whole host of other technologies involved in planning and treatment as well: CT, PET-CT, MR, MLCs of various designs, film scanners, chambers, diode and chamber arrays, phantoms simple and complex.
When a hospital acquires new equipment, what happens, more often than not, is that the clinical staff never gets any meaningful experience working on the equipment until someone’s life depends on it. Therapists get shown the rudiments of IGRT by a vendor trainer (physicians sometimes get no training whatsoever), and are expected to be treating patients like experts the next day. 4DCT and gating equipment gets installed, sits unused for 6 months, then the very first patient chosen for gated delivery is an SBRT lung getting 60 Gy in 3 fractions. IMRT and SRS QA phantoms involving complex hardware and software components sit in their boxes until the night before patient treatment.
In many cases, the new technology can do more harm than good, if it is used improperly. I have seen confused therapists using cone-beam CT for the first time, making large and incorrect patient shifts they wouldn’t have considered during conventional setups. I have seen physicists running IMRT QA on equipment without receiving any training on it, and completely misinterpreting the results.
The implementation of any new technology should include some ‘grace period’ where the staff gets to practice in less-critical situations (recognizing that all patient treatments are critical). Run 4DCT scans and perform gating on regular lung patients before you rely on this technology to guide radiosurgery. Use your IMRT/SRS QA phantom on test cases (preferably covering a broad range of target sizes and degrees of complexity) before you have a patient coming in the next morning.
This sort of dry run testing shouldn’t be treated as something to do “when I get around to it.” Staff time for this testing should be scheduled and that schedule protected by management. Time for adequate in-house testing should be part of the budget of any new technology purchase.
Vendors could also help the process along- for example, they could provide a broad range of anonymized patient image data for the therapists to practice with for IGRT image registration. Again, such a project involves some expense, but you would think it would be well worth it to the vendors to ensure that clinics are using their equipment safely and effectively.
Finally, each new version of hardware and software should spur a new round of training and assessment, especially for newer technologies where there can be substantial changes from one version to the next.
Hospitals are willing to spend tens of thousands to millions of dollars acquiring new technology. Yet few are willing to spend a few thousand more to give their staff the time to learn to use them properly. Time is money, but time is also safety, efficacy, and for some patients, life and death.
That’s all for now,
Ron
Bystander effect
Posted by ron in Commissioning, Medical Physics, Misc, Quality Assurance, Radiation Oncology on March 1, 2012
Hello again.
I just returned from the 2012 SRS/SBRT conference, and I learned a new word- ‘abscopal’. The word is derived from the Latin roots ‘ab’ meaning ‘away from’, and ‘scopos’, meaning ‘target’. The effect described is the surprising effect that radiation can sometimes have on cancer adjacent to, or even widely separated from, the primary target. This concept, first described in publication in 1909(!), has gained new relevance in the era of stereotactic radiosurgery (SRS) and stereotactic ablative radiotherapy (SABR).
Back in the early days of radiation therapy, treatments were limited by the low (kV-level) energy of the radiation then available. It was often not possible to deliver effective therapy to deep-seated tumors because of excessive doses received at skin level. In order to mitigate this, a technique called ‘grid therapy’ was developed, where the radiation field was partially blocked, typically delivered through a lead block with a grid of 1 cm holes drilled into it. This technique allowed high doses to be delivered to at least part of deep seated tumors, while being more tolerable at skin level.
Often, the treatment was surprisingly effective at shrinking large, bulky tumors, even though the radiation was only being delivered to a small fraction of the total volume. At the time, no one knew why this happened, or why it was more effective in some patients than others. When higher energy machines (Cobalt 60 machines and linacs) became available in the 50’s and 60’s, grid therapy was largely abandoned. A few departments still do grid therapy for isolated palliative cases, and often see remarkable tumor shrinkage, but until recently little serious study of the technique has been done.
More recent work has begun to decipher exactly what is happening with grid therapy, and how it may be relevant to recent work in radiosurgery. It is accepted now that the high fractional doses given in SRS and SABR have both direct and indirect effects on cancer tissues, directly by causing disruption in cellular function and division in cancer cells, and indirectly by destroying epithelial cells (for example, blood vessels) that support the cancer. Recent work in cell biology has shown that these same high doses cause cancer cells to release cytokines that promote apoptosis (programmed cell death) in endothelial cells.
At the conference, Mansoor Ahmed of the University of Miami described experiments he had performed where a mouse was implanted with tumors on both legs. One tumor was treated with grid therapy to a dose of 10 Gy, the other was left untreated. As expected, the treated tumors began to shrink after therapy. Amazingly, the untreated tumors began to shrink, too. However, if one leg tumor was fully treated with an open field to the same dose, the treatment shrank the treated tumor but had no effect on the untreated tumor.
This ‘bystander’ effect may enhance the ability of high, ablative doses of radiation to destroy tumors, particularly for patients with healthy immune systems. Many issues remain with the effective application of this therapy in patients, including how best to quantify and predict the effects in terms of biologically effective dose, and how this therapy might be effectively combined with more conventional therapies to deliver non-palliative treatments. To me, it’s just fascinating that some of the oldest concepts in radiation therapy may have relevance to the newest technologies in the field. Stay tuned.
That’s all for now,
Ron
Reading List- The Emperor of All Maladies
Posted by ron in Medical Physics, Misc, Pathways on January 30, 2012
Hello again.
I have been reading The Emperor of all Maladies, the award-winning ‘biography of cancer’ by Siddhartha Mukherjee. Mukherjee is a medical oncologist and researcher at Columbia University. He claims he was inspired to write the book by a patient, who wanted to better understand the disease she was fighting. Mukherjee quotes Sun Tzu’s the Art of War: “If you know your enemy and know yourself, you will not be imperiled in a hundred battles”.
The book begins with the initial description of cancers by ancient Egyptian and Greek physicians and ends with the stunning recent advances in the knowledge of cancer as a genetic disease, and genetically-targeted therapy drugs like Herceptin. As it turns out, these advances came both from knowing our enemy and knowing ourselves, since the processes used by cancer cells to grow and spread are often modified versions of the processes used in the growth of normal tissues.
I am often impatient reading science books written for a lay audience, but this book was engaging throughout, not just for its science but for the colorful cast of characters one meets along the way. There’s the cocaine and morphine-addicted surgeon William Halsted, who pioneered radical mastectomies, an operation that in many cases turned out to be needlessly aggressive. Who knew that the initial, promising results of lumpectomy plus radiation were first published in 1927?
The book is honest enough to deal with the failures of cancer therapy as well as its successes. The tragic story of the STAMP regimen in high-dose chemotherapy is a case in point. After very positive initial results were published on the effectiveness of high-dose chemotherapy in breast cancer, breast cancer advocates pushed for ’compassionate’ treatment of women before definitive clinical trials could prove its effectiveness. Thousands of women, most outside of clinical trials, were subjected to a highly toxic, aggressive therapy that conferred no benefit. All of this was based on the incredible, and as it turns out fraudulent, clinical data of a single South African doctor.
I must confess, I was largely unaware of much of the history discussed in this book, even the events that occurred when I was in graduate school in a cancer research hospital. Current training of medical physicists includes very little discussion of surgery and chemotherapy- shouldn’t we know more about the major therapy options in our field?
Along the same lines, I was surprised by the almost complete absence of radiation therapy from this book. Indeed, the most recent development in radiation therapy discussed in this book is the use of hemibody radiation in the 1970’s. There is no mention whatsoever of the advances in conformal therapy (IMRT, IGRT, radiosurgery) since that time. I kept wondering as I read this book if this was typical of the perspective of medical oncologists. We would all do well to know our friends, as well as our enemies, a little better.
That’s all for now.
Ron
Safety in Advanced Radiation Therapy part 2
Posted by ron in Medical Physics, Misc, Quality Assurance, Radiation Oncology on January 4, 2012
Hello again.
Previously I had blogged about a paper from Harvard (Margalit et al, 2011) on the impact of the introduction of IMRT on the number and type of treatment delivery errors at Brigham and Women’s Hospital in Boston. This month, a new paper from my own institution, the University of Pittsburgh Medical Center (UPMC), adds to this discussion.
Olson et al (2012) looked at data on treatment errors across a large network of academic and community practice centers run by UPMC over a period of three years. They identified errors or potential errors in both IMRT and conventional therapy. They also graded the incidents on an error severity scale, in order to determine whether advanced technology influenced either the number or the severity of the errors seen.
The paper also addresses the rather unique nature of the UPMC network, where IMRT planning is performed at a centralized facility (D3) and a centralized radiation physics division seeks to ensure equivalent quality of care at a large number of clinics (3 academic centers and 16 community practices were involved in this study). Similar to Harvard, a non-punitive error-reporting system is in place at all centers.
The clinical error severity scale (CRESS) employed in this study includes both potential and actual treatment delivery errors. For example, an error found and corrected before the first dose fraction was delivered would be given a score of 1, while an actual dose delivery error that was corrected by altering the dose delivered in subsequent fractions would be given a score of 3. There were no errors resulting in injury or death (scores 8-10) seen in this study.
Again, similar to the Harvard study, the use of IMRT resulted in a markedly lower rate of treatment delivery errors, roughly half the number associated with 3D treatment delivery. The errors with IMRT were also less severe. The rate of error was reported per course of treatment rather than per fraction (reported in the Harvard study), so the numbers are not directly comparable between the two papers.
The study found no difference in error frequency between the academic and community centers. As in the Harvard study, they found no change in the error rate with time, despite the implementation of 39 system-wide policy changes in response to treatment delivery errors over the course of the study.
In the Harvard study, the start of the study period coincided with the introduction of IMRT. In the UPMC study, IMRT and the Quality Improvement committee had been in place for several years before the start of the study period, which may in part explain why no significant change in error was seen during the study.
This paper uses a severity scale for treatment errors and potential errors, while the Harvard paper divided errors into categories (eg patient setup errors, accessory errors, errors in machine settings). It would be good for a national body to further develop a national error reporting system, with categories and a severity scale- the more information the better.
One question left not fully answered by these two papers is the relative effectiveness of the error reporting and mitigation systems put in place. In both papers, the error rate started low and stayed there throughout the period studied. In both clinics, error reporting systems were already well established at the start of the study period. While it is comforting to learn that the introduction of high technology treatment delivery has improved the error rate, it would also be interesting to learn whether the error rate may be further reduced by other interventions, for example the use of checklists. (If you haven’t already done so, go out and purchase and read “The Checklist Manifesto” by the physician and writer Atul Gawande. It is a short book and well worth your time.)
That’s all for now.
Ron
References
Olson, AC et al,” Quality Assurance Analysis of a Large Multicenter Practice: Does Increased Complexity of Intensity-Modulated Radiotherapy Lead to Increased Error Frequency? “, IJROBP vol 82, No. 1, pp e87-e92 (2012)
Magalit DN et al, “Technological Advancements and Error Rates in Radiation Therapy Delivery”, IJROBP vol 81, No. 4, pp e673-e679 (2011)
The Biology of FFF
Posted by ron in Misc, Radiation Oncology on November 22, 2011
Hello again.
Radiotherapy and Oncology recently published a special
edition on the frontiers of radiation biology, and, as usual, things on the
frontier can get a little messy. The
journal contained two consecutive articles with seemingly contradictory
results, relating to the new high dose rate beams (flattening filter free, or
FFF) available on new linacs like the Varian Truebeam.
I say ‘seemingly’ contradictory because the articles deal
with different experimental setups, and use different cell lines, so the data
are not exactly equivalent. Such results
are not unusual in biology (said the smug physicist), but rather than
indicating an error, they may point to new information about the response of
cells to radiation damage.
The FFF beams differ from regular photon beams in both their
profile and the amount of dose per individual pulse (for any nonphysicists
still reading, linear accelerator radiation is delivered in short, microsecond
time scale pulses, with different dose rates achieved by changing the pulse
repetition frequency or PRF). The new
FFF beams may have instantaneous dose rates as high as 300 Gy/s, about 4 times
the rate of conventional linac radiation beams.
We all have a natural bias towards papers with positive
results, so let’s start there. Lohse et
al, from the University Hospital in Zurich, Switzerland, irradiated two glioblastoma
cell lines with a single radiation fraction using two different beams from a
Varian Truebeam- the standard 10MV beam and the 10FFF beam. They found that delivering the same dose to
the cells at the same mean dose rate (10FFF beam giving a higher dose per
pulse, but a lower pulse rate), cell survival was reduced with the 10FFF beam,
and this effect was increased the larger the single fraction dose. Giving a single 10Gy fraction, for example,
cell survival in one cell line was reduced by more than 2 times in the cells
receiving the 10FFF beam vs the 10MV beam.
They next reduced the dose per pulse in the FFF beam by
placing attenuating material in the beam, until the dose per pulse matched that
of the regular 10MV beam, and repeated the experiment. This time, there was no difference in the
cell survival between the two beams. Finally, they delivered the same beam (10FFF)
at different pulse repetition frequencies, effectively changing the mean dose
rate from 4 Gy/min to 24 Gy/min. Again,
there was no change in the cell survival for any dose rate.
All this suggests that the cells are susceptible to changes
in the instantaneous dose rate of a microsecond pulse of radiation, even when
the total delivered dose and mean dose rate stay the same. The authors suggest that this may be because
the higher instantaneous delivered dose may induce a more destructive type of
damage (double strand breaks) in DNA.
Now on to the negative result. Sorensen et al, from Aarhus University
Hospital in Denmark, irradiated two different cell lines (Chinese hamster V79
cells and a human SCC cell line). The
authors didn’t have a linac with an FFF beam, but they increased the effective
dose rate to the same levels by moving their cell Petri dishes closer to the
radiation source. This effectively
increased both the dose per pulse and the mean dose rate. In this experiment, they saw no difference
in cell survival for any total delivered dose from 1-10 Gy.
Exactly how does one reconcile two such papers? The first thing to do is to wait for other
labs to repeat and confirm the results published here. The next step might be to try the methods of
one paper on the cell lines of the other, to determine whether the changes are
due to physics or the biology of individual cell lines. These results, if confirmed, might point to a
hitherto unknown way to improve therapeutic ratio. It may turn out, for example, that glioblastoma
cells are sensitive to high dose pulses, but the brain tissue surrounding them
is not. And of course, none of this may
hold together when translated into the even messier environment of a living
human being. Stay tuned.
That’s all for now.
Ron
Safety in advanced radiation therapy
Posted by ron in Misc, Quality Assurance, Radiation Oncology on November 7, 2011
Hello again.
A new paper from Harvard discusses an important question- As
radiation therapy technology gets more and more complex, is the potential for
delivery errors increasing or decreasing?
Certainly, many of the errors reported last year in the New York Times
were related to more advanced therapies like IMRT and radiosurgery. But are these sorts of errors becoming more
frequent and more severe, as the newspaper articles suggested?
In the latest online edition of the Red Journal, Margalit et
al looked at the effect of a specific new technology (IMRT) on error rates in
treatment delivery. Over the period
discussed in the article (2004-2010), the number of IMRT treatments increased
from 0 to about 31% of all treatments. The
errors tracked were only errors that occurred during treatment delivery, not
‘near misses’, or errors in planning that were caught and corrected prior to
treatment.
Harvard has put together an admirable web-based error
reporting system. A patient safety report must be logged for any unexpected
deviation. In order to promote a
culture of safety, the system is confidential and non-punitive. The reports are reviewed every month by a
multidisciplinary QI committee that is responsible for identifying contributing
causes for each error and developing or revising policies to prevent subsequent
errors.
A number of systems were put in place to reduce treatment
errors. The record and verify system was
in place throughout the duration of the study (though the center switched from
Impac to Aria halfway through the study). In addition, a dedicated staff member, the
Quality Control Therapist (QCT), reviewed all plans from a therapy perspective
after physics check but before plans went to the treatment machine. Accessories were bar-coded, with each device
scanned just before delivery of each field.
Each patient was also given a bar-coded treatment card to be presented
before each treatment fraction.
The good news is that the all of these efforts seem to have
paid off. The total error rate over 6 years of treatment was 0.06% (155/241,546
fractions). None of the errors were
deemed clinically significant. IMRT
treatments in fact had a substantially lower error rate, 0.03% vs 0.07% for 3D
treatments.
The types of errors typically seen in IMRT treatments also
differed from those in 3D treatments. Half
of the errors in IMRT were related to incorrect machine settings, while in 3D
treatments, accessory errors and patient setup errors were more prevalent.
There are several good reasons why IMRT may be less prone to
error than 3D therapy. Since IMRT does
not incorporate accessories like blocks and wedges, there is less chance that
such an accessory would be either left out or placed incorrectly. Since there is no need for an accessory
holder in IMRT plans, the gantry clearance is greater, reducing the chances of
collision with the patient or immobilization device. Some conventional plans were delivered with
manual entry of field parameters, which is generally not possible with IMRT.
Many of the IMRT delivery errors occurred when the record
and verify system was either down or overridden. Even with the use of automated
technologies for patient verification and treatment delivery, human error was
still the most common cause of treatment delivery errors. The authors make a point that bears repeating
here: “…technology cannot replace the
need for human engagement in the delivery process and adequate training.”
Interestingly, the level of error in IMRT plan delivery
started very low and never really changed over the 6 years of the study. There was a small decrease in 3D errors in
the first year of the study, then this level of error also seemed very stable
for the next five years. This is in
contrast to an earlier study from Duke (Marks et al, IJROBP 2007), where they
noted that errors in non-MLC linacs increased after the introduction of
MLC-equipped linacs, suggesting that when therapists got used to more automated
systems, they became less careful with older equipment.
Overall, the paper shows the level of treatment delivery quality
that may be reached with good practices.
It is to be hoped that systems of reporting and dealing with treatment
delivery errors as discussed in this paper will become the norm in radiation
oncology, as well as in other fields of medicine.
That’s all for now,
Ron
References:
Margalit, DN et al,
Technological Advancements and error rates in radiation therapy delivery,
IJROBP 2011 V81, pp e673-e679.
Marks LB, Light KL, Hubbs JL, et al. The impact of advanced
technologies on treatment deviations in radiation treatment delivery. IJROBP
2007 V69, pp 1579–1586.
Psychosocial Support and Cancer
Posted by ron in Medical Physics, Misc, Radiation Oncology on October 7, 2011
Hello again.
We have a book club at work, and for this I have been
re-reading one of my favorite books by one of my favorite writers, The Man Who
Mistook His Wife for a Hat, by the neurologist Oliver Sacks. The book is a collection of case histories
of some fascinating patients Sacks has encountered in his career as a
practicing neurologist in New York City.
The title story, for example, is about a music teacher with
prosopagnosia, an inability to process visual information so severe that he
literally mistakes his wife for a hat.
Amazingly, in spite of this, the man was able to carry on teaching
music, and used music to organize what would otherwise have been impossible
tasks of daily life.
Sacks’ central thesis in this collection of ‘clinical tales’
is that his patients’ conditions cannot and should not be separated from their
lives as a whole. In medicine,
particularly in radiation oncology, we often think of our patients in terms of
a disease, or worse, we see them as a set of tomographic images on a computer
screen, not as living, breathing human beings.
But are we really doing our patients a disservice by looking at their
conditions in the cold, rational light of science?
Sacks has taken a lot of criticism from his fellow
neurologists for what they see as an anecdotal or ad-hoc approach to
neurology. They note that great strides
have been made in medicine through controlled clinical trials, where patients
are indeed reduced to a diagnosis and a cold, objective set of characteristics-
age, stage of disease, performance status, comorbidities. Only by doing so, they argue, can we
determine what is effective medicine, and offer the best hope of a cure to our
patients.
It is harder to think of the effect of one’s daily life in
oncology versus neurology, yet there is a growing body of information that
suggests that a patient’s psychosocial status can indeed have an effect on both
their chances of getting cancer and their response to treatment. There was a meta-analysis
of this effect published in Nature Clinical Oncology 2008. It is known, for example, that stress can
weaken the immune system, and the release of stress-related hormones can have a
direct effect on cancer cells. A
diagnosis of cancer will itself cause distress in patients, and in severe cases
may provoke anxiety, sleeplessness and loss of appetite that may worsen a
patient’s condition.
The analysis of the effects of stress is made more difficult
because there hasn’t been a consistent way to assess and score psychosocial
status between different studies. A review
presented at ASTRO this year found 45 different scales used to measure distress
in cancer patients. There is a very
simple ‘distress thermometer’, a 10-point scale recommended by the NCCN, but it
has not been widely adopted. One
wonders whether better assessment of psychosocial distress might improve
analysis of many clinical trials, and whether better treatment of distress
might improve trial results.
I started thinking about this earlier this summer, when my
Uncle Wilf passed away from cancer at the age of 93. He had lived the sort of ordinary/extraordinary
life typical of the ‘greatest generation’- World War II aviator, successful
businessman, choral singer (I trace my own love of Gilbert and Sullivan
operettas to him), avid golfer and curler (that strange Canadian sport much
loved among the legendary medical physics department of Johns and Cunningham). He lived a long and vigorous life surrounded
by a large family and many good friends.
It would seem that such social supports may not only make life happier,
they may make it healthier and longer besides.
That’s all for now.
Breast IMRT
Posted by ron in Medical Physics, Misc, Radiation Oncology on September 20, 2011
Hello again, and apologies for the long summer break between posts.
The topic of IMRT billing for breast has recently come up at our institution, as a change in health care coverage is likely to remove IMRT reimbursement for the vast majority of cases. Patterns of coverage for breast IMRT vary widely around the country, and our own area has probably been more generous than most until now. Our local health systems are now faced with the problem of how to proceed from here.
The use of IMRT in breast caused some controversy almost from the beginning. There were initial
promising planning results (for example, from Vicini et al at William Beaumont) demonstrating better uniformity of dose, reduced dose to heart and lung, and lowered scattered dose to the contralateral breast. Later, randomized clinical trials comparing IMRT to 3D (some of the few randomized trials ever done in IMRT) showed lower toxicity and better cosmesis using breast IMRT. A nice, brief review
of the available evidence for breast IMRT was published recently by Seminars in Radiation Oncology.
However, there were concerns that these somewhat modest gains didn’t justify the greatly increased cost of IMRT delivery (at least, to health insurers), as expressed in an early editorial
in the red journal. Also, the possibility of greater leakage dose inducing secondary cancers in a relatively young patient population also caused concern.
The actual cost of delivery of breast IMRT (as opposed to dollar value billed to health insurers) is only slightly larger than planning with hard wedges. Unlike the early days of IMRT, the use of IMRT no longer requires the use of specialized planning systems or add-on collimators; almost all centers in the U.S. are fully capable of delivering IMRT with the machines they use for standard therapy. There is some additional cost in QA by physics, but the cost of delivery of the therapy is no greater than 3D conformal planning, and may even be less, since iMRT breast plans can be delivered more
quickly than plans with hard wedges.
Planning for breast IMRT may take more time than simple 3D planning. However, a recent article in the red journal suggests that the process of breast IMRT planning may be largely automated. Using scripting tools available with the Pinnacle planning platform, Purdie et al developed a fully automatic breast IMRT planning technique that was able to produce satisfactory results in 99% of the cases studied in an average time of about 7 minutes.
So what is a hospital to do, if IMRT for breast has already been in wide use, and billing is suddenly taken away? Some health insurers will not even allow you to bill 3D planning for a patient if you use IMRT plans. Do we go back to hard wedges? If we acknowledge that IMRT plans are better for our patients, do we bite the bullet and plan IMRT anyway? Or do we go a compromise route, doing some
form of non-optimized breast planning using the MLC as a virtual compensator?
The longer term solution, of course, is reform of the billing system itself, to remove the incentives for giving a patient the most expensive therapy and provide incentives for delivering the best therapy. But regulations move much more slowly than technology does, and that is not likely to change anytime soon.
That’s all for now.
Effectiveness in Radiation Therapy
Posted by ron in Medical Physics, Misc, Radiation Oncology on July 21, 2011
Hello again.
A recent editorial in the Red Journal (1) once again raises the important question: How much of our current effort in creating ever more conformal, targeted, high-dose radiation therapy is actually improving treatment outcomes for our patients?
The authors examined dose escalation in prostate cancer therapy. Prostate cancer is usually a slow-developing disease, such that it takes large trials and long follow up to determine benefits of new therapies. On the other hand, it is where many new technologies are first studied- much of the early work in IMRT, IGRT, protons, and hypofractionation was centered on prostate cancer.
The evidence reviewed for this editorial seems to show that for low and intermediate risk prostate cancer there is no demonstrable benefit in dose escalation in terms of either disease-specific survival or overall survival. While some studies reviewed in this article (2,3) have shown improved freedom from biochemical failure at higher doses, this has not translated into improved survival.
Improved conformality in treatment planning and the use of image guidance in treatment delivery can reduce toxicity levels as the dose is escalated, but if dose escalation provides no benefit, are these other technologies simply enabling an unnecessarily aggressive treatment? Indeed, there are some publications showing that conformal planning and IGRT can lead to more treatment failures if PTV margins are reduced too far(4).
As health care consumes an ever larger portion of GDP, efforts are underway to determine the cost-effectiveness of medical interventions (an informative interview on the subject with Harvard’s Milton Weinstein can be found here) How long can radiation oncology justify using the latest and most expensive technology (protons) on prostate cancer when there is no evidence to suggest these patients will benefit from it?
- Schulz, R.J and Kagan, A.R. , “ Dose Escalation in the Radiation Therapy of Prostate Cancer “, IJROBP 80 (5), pp1289-1291,2011.
- Kuban, D.A. et al, “Long-term failure patterns and survival in a randomized dose-escalation trial for prostate cancer. Who dies of disease?”, IJROBP 74 pp. 1–8, 2010.
- Eade, T.N. et al, “What dose of external-beam radiation is high enough for prostate cancer”, IJROBP 68, pp. 682–689, 2007.
- Engels, B. et al, “Conformal arc radiotherapy for prostate cancer: increased biochemical failure in patients with distended rectum on the planning computed tomogram despite image guidance
By implanted markers”, IJROBP 74 (2) pp. 388–391, 2009.
Cell Phones and Risk
Posted by ron in Medical Physics, Misc, Radiation Oncology on June 29, 2011
Hello again.
Recently, the World Health Organization (WHO) released a report classifying cell phones as a possible carcinogen. The WHO employs 5 classes of carcinogen, ranging from 1 (probably carcinogenic) to 4 (probably not). Cell phone radiation is in class 2b (possibly carcinogenic), a category which also includes coffee and gasoline fumes. My own gut reaction to the report was that the finding was probably premature, given that there isn’t as yet any clear mechanism by which cell phone radiation might cause cancer. There has of course been a huge increase in cell phone use in the last 20 years, but no observable increase in brain cancer over the same period. However, the long latency period of some cancers may mean that we just haven’t seen the increase yet.
What is the evidence that cell phone radiation is carcinogenic? There are some in vitro studies showing that RF radiation of the same frequency and intensity as cell phones can cause biologically significant changes in cell cultures, such as an increase in heat shock proteins (1), although other studies have failed to replicate some of these results (2).
There are also a number of case control studies, large population-based studies of cell phone use and risk of cancer. Most of the studies were part of a large European effort called INTERPHONE (summarized in 3), which has been co-funded by governments and the cell phone industry. (Note that the industry has provided funding but plays no part in the running of the studies). None of these studies has shown a clear link between cell phones and cancer, but some subgroup analyses (longer term users, users in rural areas where the RF signal is stronger) have shown significant increases in risk.
I am always leery of results from subgroup analyses, ever since hearing a lecture from one of my professors in grad school, Ian Tannock, who was critical of the way many clinical trials were run. His belief on subgroup analyses was that if you ran enough of them, you could always find a positive result. Unless the subgroup is clearly part of the original design of the trial, any results from subgroups should be taken with a grain of salt. This has also been the subject of a clever xkcd cartoon.
At my own institution, the University of Pittsburgh School of Medicine, the director of the cancer centers, Ronald Herberman, released a memo in which he urged the staff to take some precautions to reduce cell phone exposure. These include:
-using hands free, texting, or Bluetooth, which reduces the RF exposure by about 100 times
-avoiding long calls, or using the cell in areas of low signal, which causes the RF output to increase
-not giving cell phones to children
I have become more cautious about cell phone use myself since researching this question for the blog. Although the risk of getting cancer from a cell phone is unproven and small, it seems to me that taking a few simple, inexpensive precautions that are already available (speakerphone, Bluetooth) makes a lot of sense until science can answer the question one way or the other. And to my daughter- you’re just going to have to wait a few more years until you can have one.
That’s all for now.
Ron
1. Kwee et al, Changes in cellular proteins due to environmental non-ionizing radiation. I. Heat-shock proteins. Electro Magnetobiol 20 (2): 141 – 152 (2001).
2. Dawe et al, Continuous Wave and Simulated GSM Exposure at 1.8W/kg and 1.8 GHz do not Inducehsp16-1 Heat-Shock Gene Expression in Caenorhabditis elegans, Bioelectromagnetics 29:92-99 (2008).
3. The INTERPHONE Study Group. Brain tumours risk in relation to mobile telephone use: results of the INTERPHONE international case-control study. Int J Epidemiol 39 :675-694 (2010).
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