Sky-high medication prices are emerging as a political issue. Costs of cancer drugs have shot so high that patients are struggling to pay for their meds. Hospitals are balking, insurers are denying some coverage. Even doctors are protesting.
Meanwhile, the biotech field is abuzz with promising new tools, drugs and speculation. Some wonder if precision medicine is worth so much effort and investment including tax dollars, when already it seems like we can't pay for the treatments we've got. Many people, including physicians, don't understand it.
My first concern is medical: Do personalized, mutation-matched drugs really help? And practical: If the meds are good, can they be rendered affordable and delivered to patients who'd benefit?
So I've decided to write a few columns on precision medicine, with a focus on cancer. And before I get into the nitty-gritty of science, research and what needs to change – in medical education and clinical trials – for precision medicine to become affordable and near-universally helpful, I'll put my viewpoint out, here: I think precision medicine is the future, at least in oncology.
Precision medicine is good for everyone: It will help cancer patients by sparing them toxicity (and time) of trying ineffective drugs. And it will help society, ultimately, in part by reducing healthcare costs.
I am not naïve about this field. Rather, I come to it from the perspective of a doctor who prescribed chemotherapy "in the dark" from 1990 through 2006. When I practiced oncology, we had few ways to anticipate who would respond favorably to chemotherapy. We had fewer drugs, and fewer "handles" on our patients' conditions.
The basic idea of precision medicine in oncology is to approach cancer with multiple, smarter drugs, much like the medication cocktails that have proved so effective in HIV. Anti-viral meds have changed what was an AIDS patient's apparent death sentence, at diagnosis 30 years ago, to what's now a chronic illness. It's possible – and even likely – we can do better, for most tumors forms. If we can use technology wisely, the treatment course will be minimized.
With modern pathology tools, including genomic testing of each tumor, and each patient's inherited DNA – along with other studies, of protein and other features of the cancerous cells – oncologists will tailor regimens in each case. With emerging liquid biopsy methods, they will monitor patients' cancers for growth or change with blood tests.
The capacity to fingerprint individuals' tumors – before treatment, and to see if and how they respond to treatment – is an old oncologist's dream. It might be a patient's, too. The problem is, we're not there yet.
A recent letter in the Journal Of Clinical Oncology, on a report revealing the difficulty of carrying out a studies organized by genetic mutations, rather than old-fashioned cancer types – like "small-cell lung cancer" or "thyroid cancer," went by this title: Basket Trials: Just the End of the First Quarter. I know enough about sports to appreciate the author's point: it's far too early to draw conclusions.
You might wonder, if we're just starting out in precision medicine, how can I be so confident that precision medicine will save money in cancer care?
The NCI estimates costs of U.S. cancer care approximate $157 billion (in 2010 dollars) and indicates this number will go up, as our population expands and lives longer. According to a report on global oncology spending released last spring by the IMS Institute for Healthcare Informatics, considered here, worldwide spending on cancer medication in 2014 surpassed $100 billion. These are big numbers, without even accounting for the added costs of lost productivity, when people die prematurely, and the emotional toll on friends and family.
What these figures tell me – as someone who sees modern healthcare as a right, not a privilege – is that our society needs distribute medical resources more judiciously. Leaders in policy, doctors, patients and advocates need to think carefully, collectively, about the use of expensive drugs at the very end of life in very old people, for instance. Med-ethics needs to enter this discussion, whether or not philosophers and politicians can distinguish antibodies from CAR-T cells.
For some cancer patients, precision medicine will lead to less treatment. An example is the recent report on OncotypeDx. This test provides molecular information that enables 16% of early-stage breast cancer patients to skip chemotherapy. Without this and other kinds of precision testing of tumors (there are many in the works), which should inform treatment, more patients with early-stage disease would get aggressive care.
For most cancer patients, precision medicine will lead to discrete courses of meds after surgery only (or no surgery, or no meds, depending on the cancer's characteristics). As blood assays, a.k.a. liquid biopsies, for monitoring become more accurate and cheaper, pulling back on big-C treatment will become easier and safer, because doctors will be more able to monitor patients for relapse, rather than treating so many to prevent that possibility.
Yes, there will be some patients who will need life-long cancer treatment. And there will be some who won't outlive their tumor. Not every case will be curable. But in general – if patients can get rapid and accurate diagnoses (an issue in itself), and access to the best meds provided by well-educated physicians – most people should be able to live with, or beyond, their cancer.
For most cancer patients, expenses will drop because they'll get likely-to-be-helpful meds within days of their diagnosis, and skip over many toxic treatments that now represent the standard of care, and which too often serve as hurdles for them to pull through, physically and financially and in every other way, before they're even allowed to try the new stuff. Those costs – of delaying precision-based or matched treatment – include hospitalizations, intravenous lines, complications of those, steroids and other meds to lessen side effects, nursing and some deaths.
Why wait until a person with cancer has resistant, stage 4 disease to prescribe the best treatment – if scientists now know, or in three years will know, what the exact best treatment is for that person's unique tumor?
Don't get me wrong. I've read the early, published reports. Like the recent paper in Lancet Oncology in which 741 patients, all with previously-treated, advanced malignancies, were randomized only then to receive a single targeted therapy or their physician's choice of a standard old treatment. That study failed to show an advantage of precision medicine. But the patients got only one drug, and were heavily treated before entering the study. The main finding is that giving single drugs to patients with refractory, end-stage tumors doesn't work well.
The kind of precision medicine I'm talking about involves smart combinations of drugs, including medication cocktails provided by different companies.
Consider the promising experimental kidney cancer drugs about which I recently wrote. In most healthcare systems, these cost over $100,000 per year of treatment, for each drug alone. But nivolumab and cabozantinib each helped only a fraction of the patients in each study. How much better would everyone fare, and how much lower would the total expenses be, if before starting those medications doctors could determine who'd respond, and then match patients to those drugs, up-front?
What I see as realistic is development of small oncology drugs and biological agents that don't cost so much to manufacture and distribute. I acknowledge the expense, including risks, of developing new drugs. This is a huge issue in pharma now, an oft-cited reason for insanely high prices. Getting around this barrier may require an overhaul of the randomized clinical trials model, the gold standard by which I was trained and how most MPHs and old fashioned oncologists, among others, evaluate new and old treatments.
Over time the costs should drop, like for smartphone technology, what my dad – a chemistry major and retired physician – in the months before he died, called "magic."
Some of the ways cancer care costs will go down, as precision medicine evolves, will be by reduced use of radiation oncology (this statement may cost me some friends in that space, and I intend to expand on it later). Also, we may need to focus on small drugs that are not individualized biologic remedies, like T-cells removed from patients and doctored in labs (same; sorry, guys.) Because off-the-shelf pharma products, however mixed, are cheaper to make and distribute and monitor for quality control, sterility, etc.
Which means that an essential topic in precision oncology is understanding differences between cancer drugs like antibiotics (and some cancer drugs are, indeed, antibiotics) or more complicated but standard biologics, like antibodies or, in the future, RNA inhibitors, which can be "personalized" by reason of their matching a cancer's vulnerable spot, such as a mutation or turned-on receptor-type protein, and treatments that are personalized in the deeper and harder-to-manufacture sense of coming from the cells of a human and then being processed in a lab for one, particular patient, along the lines of an autologous stem cell transplant. These individual patient-derived biological drugs are out-of-sight costly, and possibly less precise, although they may be most effective in some situations – all of which needs be considered.
My point for now is that precision medicine in oncology is a realistic goal if we're willing to challenge the status quo, think creatively and carefully, both. (Preventing cancer is a better goal, for the record. But environmental oncology and cancer prevention has fewer investors and scientists and doctors working in the field. It is taking too long.) And if pharma, investors, FDA officials, oncologists, other doctors, patients, IT people, everyone – all the "stakeholders," a term I dislike using in healthcare – cooperate, to make this happen, and be a good thing.
In the long term, everyone will benefit by cancer science that links modern drugs to individual patients' tumors.
