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Understanding Intersurgeon Disagreement in Lumbar Spine Surgery

This hybrid study characterizes intersurgeon disagreement in lumbar spine surgery by synthesizing literature on treatment variability and introducing the Surgical Gray Zone Index (SGZI), an entropy-based framework that quantifies surgical decision-making uncertainty from published data.

Original authors: Benjamin Costantino

Published 2026-07-14

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Benjamin Costantino

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you walk into a hospital with a sore lower back. You see Surgeon A, who says, "We need to fuse your spine with metal screws!" You leave, see Surgeon B, and they say, "No way, let's just take out the pressure and leave the bones alone." You see Surgeon C, who suggests a mix of both.

This isn't just a difference of opinion; it's a massive, confusing fog known as the "Surgical Gray Zone." A new study by Benjamin Costantino dives into this fog to see just how thick it is, using a clever math trick to measure the chaos.

The Great Back-Operation Lottery

Lumbar spine surgery is huge in the U.S.—over 450,000 fusion procedures happen every year. But here's the kicker: where you live and which surgeon you see matters more than your actual back problem.

The paper points out that in some regions, fusion rates are ten times higher than in others. If you live in the South, you are much more likely to get a fusion than if you live in the Northeast. It's like a lottery where your ticket is your zip code. One study found that for a specific back condition, the rate of adding fusion surgery ranged from 82% in some states to 98% in others. That's a huge gap for the same medical issue!

The "Expert" Guessing Game

You might think, "Well, maybe the surgeons who recommend fusion are just better at spotting who needs it." The paper tests this idea and finds it's probably not true.

In a major study called NORDSTEN-DS, researchers asked surgeons what they wanted to do for 222 patients. Then, they randomly assigned patients to get either the surgeon's preferred treatment or the opposite one. The result? It didn't matter. Patients who got their surgeon's "favorite" treatment did just as well (or poorly) as those who got the opposite.

This suggests that when a surgeon says, "I think this patient needs a fusion," they might be guessing based on their own habits or training rather than a clear medical rule. Orthopedic surgeons and neurosurgeons often disagree on the same patient, and even surgeons with decades of experience can't seem to agree on the best path.

The Math of Confusion: The "Gray Zone" Meter

To measure this confusion, the author invented a tool called the Surgical Gray Zone Index (SGZI). Think of it like a "disagreement thermometer."

High Heat (High Entropy): If half the surgeons say "Fusion!" and the other half say "Decompression only!", the thermometer hits the max. This means total uncertainty.
Cool Down (Low Entropy): If almost everyone agrees on one path, the thermometer drops.

The paper used this meter on real data from two studies:

The 2016-2019 Shift: In 2016, the disagreement meter was high (0.911). Surgeons were split. By 2019, the meter dropped to 0.456.
- Wait, isn't that good? The paper argues no. The surgeons stopped disagreeing, but they all started agreeing on the wrong thing. They all started choosing fusion, even though two major scientific trials had just shown that "decompression only" was just as good and safer. The "consensus" moved away from the evidence, not toward it.
The Specialty Split: When looking at scoliosis surgery, orthopedic surgeons were split almost perfectly down the middle (49% fusion vs. 51% no fusion), giving a max disagreement score of 1.000. Neurosurgeons were slightly more united, but still very split.

The "Why" Behind the Chaos

Why is everyone so confused? The paper suggests it's not about the patient's back, but about the surgeon's background:

Training: Where you went to school and what specialty you picked (Orthopedics vs. Neurosurgery) predicts what you'll do.
Location: Your zip code dictates your odds of getting a fusion.
Habits: Surgeons who do more surgeries tend to use fusion more often, even if it's not strictly necessary.

The paper also notes that things like anxiety, depression, or chronic pain use (psychosocial factors) affect how patients feel after surgery, but we don't really know if these factors should change which surgery a doctor recommends.

The Bottom Line

The main takeaway is that agreement doesn't mean correctness. Just because surgeons stop arguing and all start doing the same thing (like fusing spines) doesn't mean they've found the perfect answer. In fact, they might have all agreed on a path that ignores the best scientific evidence.

The paper suggests that until we have better tools to figure out exactly who needs what, we should rely on shared decision-making. This means surgeons should be honest about the uncertainty: "We don't have a perfect rulebook here. Here are the options, here are the risks, and here is what I would do—but the final choice should be yours."

The study doesn't claim to have solved the mystery of back pain. Instead, it shines a flashlight on the "Surgical Gray Zone," showing us that sometimes, the biggest variable in your surgery isn't your spine—it's the surgeon sitting across from you.

Technical Summary: Understanding Intersurgeon Disagreement in Lumbar Spine Surgery

Problem Statement
Lumbar spine surgery, particularly for conditions like degenerative spondylolisthesis and spinal stenosis, is performed frequently in the United States, yet it is characterized by substantial and unwarranted variation in practice patterns. Significant disagreement persists among surgeons regarding fundamental clinical questions: which patients require surgery, whether to perform decompression alone or add fusion, and when fusion is appropriate. This variability leads to disparate patient outcomes, inflated healthcare costs, and challenges in establishing evidence-based guidelines. The core problem is that a patient's likelihood of receiving a specific procedure (e.g., fusion) often depends more on geographic location and the specific surgeon consulted than on the underlying clinical condition or high-quality evidence.

Methodology
This study employs a hybrid research design consisting of two distinct components:

Narrative Synthesis: A purposive review of existing literature, including landmark randomized controlled trials (SPORT, NORDSTEN, SLIP), national database analyses (Dartmouth Atlas, Medicare, National Inpatient Sample), surgeon surveys, and registry data. This section documents the scale of geographic and surgeon-to-surgeon variation and explores drivers such as specialty training, psychosocial factors, and surgeon preference.
Quantitative Synthesis (SGZI Calculation): An original application of the Surgical Gray Zone Index (SGZI), an entropy-based framework designed to quantify uncertainty in surgical decision-making. The authors calculated Shannon entropy ( $H = -\sum p_i \log_2(p_i)$ $H = - \sum p_{i} lo g_{2} (p_{i})$ ) using explicit, extractable treatment proportions from published aggregate data.
- Eligibility Criteria: Only studies reporting specific numeric proportions for discrete treatment categories (e.g., decompression alone vs. decompression with fusion) without the need for estimation or interpolation were included.
- Data Sources: Only two studies met the strict eligibility criteria: Sastry et al. (2023), reporting national inpatient sample data for lumbar stenosis with degenerative spondylolisthesis (2016–2019), and Shetty et al. (2024), reporting instrumented fusion rates by surgeon specialty for scoliosis and spondylolisthesis.
- Metric: For binary treatment splits ( $k=2$ ), the maximum entropy is 1 bit. The SGZI is normalized such that $SGZI = H/H_{max}$ . A value of 1.0 indicates maximal uncertainty (equal split between options), while lower values indicate consensus.

Key Contributions

Quantification of Disagreement: The paper introduces and applies the SGZI as a reproducible method to measure surgical uncertainty directly from published treatment distributions, moving beyond qualitative descriptions of variation.
Evidence of "Falling Uncertainty" vs. Evidence Concordance: The study demonstrates that a decrease in entropy (falling disagreement) does not necessarily equate to an increase in adherence to evidence.
Identification of the "Surgical Gray Zone": The analysis highlights specific clinical scenarios, particularly degenerative spondylolisthesis, where evidence supports decompression alone, yet practice patterns have consolidated toward fusion, creating a "gray zone" of high uncertainty that has paradoxically narrowed in the wrong direction.

Results

Scale of Variation: Geographic variation in fusion rates is extreme, with extremal ratios exceeding 10:1 across U.S. regions. Individual surgeon disagreement is high; surveys indicate disagreement rates of 64–71% for spondylolisthesis cases.
SGZI Findings:
- Sastry et al. (2016–2019): National entropy for the decompression-versus-fusion decision in degenerative spondylolisthesis declined from 0.911 in 2016 to 0.456 in 2019. This indicates a consolidation of practice toward fusion. However, this occurred despite the publication of two major non-inferiority trials (NORDSTEN-DS, SLIP) suggesting decompression alone was sufficient. Thus, consensus increased, but it moved away from the evidence-supported option.
- Shetty et al. (Specialty Variation): Entropy values varied by surgeon specialty. For scoliosis, orthopedic surgeons showed an even split (49%/51%), yielding a maximum SGZI of 1.000. Neurosurgeons showed a more lopsided split (33%/67%), yielding an SGZI of 0.915. For spondylolisthesis, neurosurgeons showed an even split (49%/51%, SGZI 1.000), while orthopedic surgeons favored fusion (74%/26%, SGZI 0.827).
Surgeon Preference and Outcomes: Analysis of the NORDSTEN-DS trial (Seip et al., 2025) revealed that patients receiving their surgeon's preferred treatment did not have better outcomes than those receiving the opposite treatment. Surgeon preferences were driven by radiographic findings (e.g., severity of listhesis) but did not translate into improved clinical results.

Significance and Claims
The paper claims that intersurgeon disagreement in lumbar spine surgery is a quantifiable phenomenon that can be measured using entropy-based metrics applied to aggregate data. The primary significance lies in the finding that consensus is not a proxy for correctness. The SGZI successfully captured a reduction in disagreement (lower entropy) between 2016 and 2019, but this reduction represented a shift toward a treatment option (fusion) that high-quality trials had found to be no better than the alternative (decompression alone).

The authors conclude that:

Unwarranted variation is driven by surgeon factors (training, specialty, geography) rather than patient factors.
The "expertise" surgeons believe they bring to individualizing treatment may be illusory in specific contexts like spondylolisthesis.
The SGZI provides a foundation for future validation studies using larger registry-level datasets to distinguish between unwarranted variation and appropriate shared decision-making.
Clinical practice should prioritize shared decision-making and transparency about uncertainty, as surgeon preference does not currently predict better outcomes in these scenarios.

The study explicitly limits its scope, noting that the quantitative synthesis is a "proof-of-concept" due to the scarcity of studies reporting extractable category-level proportions. It does not claim the SGZI is a standalone measure of appropriateness but rather a tool to measure the degree of disagreement, which must be paired with evidence-concordance measures to be clinically actionable.

The Great Back-Operation Lottery

The "Expert" Guessing Game

The Math of Confusion: The "Gray Zone" Meter

The "Why" Behind the Chaos

The Bottom Line

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