A note on protocols

Epistemic status: speculative

One thing that stands out about the history of chemotherapy is that what made it broadly effective in leukemia and lymphoma were not drugs but protocols.  Cytotoxic chemo drugs in the 1940’s-60’s had real anti-tumor effects but short-lived remissions until clinicians began administering chemo for longer periods and with combinations of drugs. 

Until working protocols had been set up, chemotherapy was highly controversial.  “As Alfred Gellhorn recently recounted to the authors, the otherwise great clinician Loeb, a giant in the field at the time, had a blind spot when it came to caring for cancer patients and testing chemotherapy. He was fond of saying to Gellhorn, rather openly, “Alfred, you belong to the lunatic fringe.”  This “lunatic fringe” of early chemotherapists persisted in trying different protocols until they got success, despite a heavy death toll.

I’m not sure if someone has made this distinction before, but there seems to be a difference between the “discovery phase” when you observe that some treatment has a desirable property (e.g. a drug has anti-tumor activity) and the “engineering phase” when you figure out how to optimize delivery of that treatment.

In the tech industry, the conventional wisdom is that you need rapid iteration for the “engineering phase” of optimizing the performance of something that already sort of works.

The problem is that rapid iteration on human patients is hard to do, and more so today than in the past.

Rapid iteration is also not particularly suited to the structure of controlled trials.  Trying lots of relatively small changes is harder at large scale and with formal standards of experimental design. It’s more the sort of thing that makes sense for case series.  But it takes a lot of independence on the part of researcher-clinicians, and I suspect that it’s not done enough.

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5 thoughts on “A note on protocols

  1. I had a friend who worked on this sort of thing. Basically trying to evaluate what set of experimental parameters to try next in order to learn as much as possible about the response function, to help people explore parameter space more efficiently when experiments are costly. Whetlab was the name. They were acquired by Twitter.

  2. Can you explain why patient-specific chemotherapy protocols that are based on a patient’s blood work aren’t a thing? For example “dose-dense” chemo seems to give better outcomes, so it would stand to reason that the dose-density should be optimized on a per-patient basis: if the patient’s CBC comes back fine, then it’s time to do the next chemo. I can understand it might be complicated for schedulers, but it seems obvious that it would improve patient outcomes. Why is this not a thing?

    • I have heard of this happening in some cases. Off the top of my head I remember that a patient-specific chemo protocol for osteosarcoma got the best survival rates (iirc 90% 5-year survival rates where standard chemo was 70%). I expect, but would have to check, that patient-specific protocols do exist but aren’t common. It seems like common sense to me too. One issue I can imagine is that it is harder to make a double-blind study (a patient is going to know how many doses of chemo they get, and there’s all kinds of extra opportunities for provider bias). It’s difficult to replicate experiments about protocols where the clinician used a lot of case-by-case judgment.

  3. Maybe mathematical modeling can help here. Franziska Michor’s group has been working on this:

    “Mathematical modeling of PDGF-driven glioblastoma reveals optimized radiation dosing schedules.”
    http://www.ncbi.nlm.nih.gov/pubmed/24485463

    “Optimization of dosing for EGFR-mutant non-small cell lung cancer with evolutionary cancer modeling.”
    http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3500629&tool=pmcentrez&rendertype=abstract

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