Johns Hopkins neurosurgeon Daniel Lubelski uses a case study to explain how decision-making tools can help guide treatment approaches for patients with spine tumors. The neurologic, oncologic, mechanical instability and systemic considerations (also known as NOMS) framework, which incorporates the spine instability neoplastic score (SINS), serves as a prediction tool that guides treatment decisions, reduces human bias and leads to better outcomes and greater success.
Hi, I'm Daniel Lubelski. I'm the director of spine tumor neurosurgery at Johns Hopkins University. Today, I'm going to be talking about why decision making tools and prediction tools in spine tumor neurosurgery is important. I'll start with a recent case that came to my attention. It was a 72 year old man who came in with urinary dysfunction, severe back pain and loss of ability to ambulate. Over the past two weeks, it came to my attention. And the question was, what should we do? The MRI showed a spine tumor that was significantly compressing the spinal cord. And the question is, how do we approach this? So the first thing we think about is the NOMS framework. No MS N stands for neurologic. We think about. Is there any neurological dysfunction? Is there myelopathy signs of cord compression? Is there ridiculed and how do we treat it to help prevent further loss of function? In this case, the patient had loss of ability to ambulate and was clearly myelopathic, which suggests an urgent indication to operate. The oncologic factors are important as well in spine tumor neurosurgery. It's important to understand what are the tumor types that are radiosensitive versus radio resistant. When we think about radio resistant tumors, we think about the need for separating the tumor from the spinal cord. Before continuing with further treatment like radiation and stereotactic radiation. In radio sensitive tumors oftentimes we could get them to urgent conventional radiation and allow for the tumor to be treated without the need for invasive surgical operations. The M component is very important as well. The M is the mechanical instability, is there a mechanical instability, is there was the structural integrity of the spine compromised by this tumor? And the way we think about that is using another acronym called the sins score. The spine instability neoplastic score tells us whether there is that compromise. It takes into consideration factors like whether it's junctional, is it at the junction? Is it at the thoracolumbar junction? Whether the vertebral body height is compromised is their erosion of the anterior cortex and the posterior elements. And those factors together give us a score scores that help us guide whether this is an unstable injury or a stable injury, whether we need to stabilize with screws or not. And then the last factor that we think about is the s or the systemic considerations. Is this patient young and healthy or old and sickly? And how do we think about that in the context of whether or not this patient will tolerate surgery? And I think it's this last portion that often times stumps, clinicians and how do we know is this person too old or too sickly or whether the combination of factors make it worthwhile to pursue surgery or to pursue other interventions. At the end of the day, our goal is to provide the best quality of life and the best oncological outcomes for patients. And so we need to think about this. Now, how do we think about the s the systemic considerations? And this is when I'm going to talk about the prediction factors, the prediction tools, the decision making guides that help us understand this. If you think about how historically we've done it, we said I use my clinical acumen, my gestalt to understand is this patient too sick or healthy to pursue surgery? The problem is that has human biases that we now understand with large studies that we've conducted showing that human biases make us prone to error. The other factors to consider is well, why don't we use the evidence? What's published in the scientific literature? So I'll say if you are obese, you have a higher risk of infection. If you are old or frail, you have more risk factors. The problem is that's too broad. Even putting people in those large categories is difficult to understand because a young person may be obese, an old person may be very healthy and fit with minimal comorbidities. So it gets me to the prediction tools using statistical tools and analysis. We're able to look at our institutional data. We're able to put together all the variables and create a calculator where I could plug in an individual's unique data points and provide a unique individualized prediction score that tells us what is the risk of infection of need for rehabilitation, risks of needing blood transfusion and other types of risks. So putting that together using these specialized calculator tools, gives the clinician more information, gives the patient more information and ultimately lets us get catered tools and operations that are best for the individual to lead to better outcomes and more success. Most importantly, these tools while they are very powerful need to be used as adjuncts to come to an institution that has vast expertise, multidisciplinary conferences where people come together and discuss these numbers, discuss these predictions and use them in combination with the expertise here at Johns Hopkins, Spinal oncology. We have such multidisciplinary conferences. So every patient is reviewed, all decisions are using the specialized tools, using the data but also using the vast expertise and network that our hospital is able to offer.
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