Proximal oesophageal cancer is commonly treated with definitive chemoradiation (CRT). The radiation dose and type of chemotherapy backbone in CRT are still under debate. The objective of this study ...is to compare the treatment benefit of four contemporary CRT regimens.
In this retrospective observational cohort study, we included patients with locally advanced squamous cell cancer of the proximal oesophagus, from 11 centers in the Netherlands, treated with definitive CRT between 2004-2014. Each center had a preferential CRT regimen, based on cisplatin (Cis) or carboplatin/paclitaxel (CP) combined with low (≤50.4Gy) or high (>50.4Gy) dose radiotherapy (RT). Differences in overall survival (OS) between CRT regimens were assessed using a fully adjusted Cox proportional hazards and propensity score (PS) model. Safety profiles were compared using the Chi-square test.
Two-hundred patients were included. Fifty-four, 39, 95, and 12 patients were treated with Cis-low-dose RT, Cis-high-dose RT, CP-low-dose RT, and CP-high-dose RT, respectively. Median follow-up was 62.6 months (95% CI 47.9-77.2 months). Median OS (21.9 months; 95% CI 16.9-27.0 months) was comparable between treatment groups (logrank P=0.88), confirmed in the fully adjusted and PS weighted model (P>0.05). Grade 3-5 acute adverse events were less frequent in patients treated with CP-low-dose RT (P=0.01).
Our study results suggest that carboplatin and paclitaxel combined with RT at a dose of 50.4Gy is the preferred CRT regimen in patients with locally advanced proximal oesophageal squamous cell cancer, showing comparable OS and a significantly more favourable safety profile when compared with cisplatin-based or higher RT dose regimens.
The authors.
Has not received any funding.
J. de Vos-Geelen: Travel / Accommodation / Expenses: BTG; Research grant / Funding (institution), Travel / Accommodation / Expenses: Servier; Advisory / Consultancy: Shire. B.T.A. de Greef: Research grant / Funding (institution): Prinses Beatrix Spierfonds (W.OR12-01). H.W.M. van Laarhoven: Advisory / Consultancy, Research grant / Funding (institution): BMS; Advisory / Consultancy, Research grant / Funding (institution): Celgene; Advisory / Consultancy, Research grant / Funding (institution): Lilly; Advisory / Consultancy, Research grant / Funding (institution): Nordic; Research grant / Funding (institution): Bayer; Research grant / Funding (institution): Merck Serono; Research grant / Funding (institution): MSD; Research grant / Funding (institution): Philips; Research grant / Funding (institution): Roche. V.E.P.P. Lemmens: Research grant / Funding (institution): Roche. V.C.G. Tjan-Heijnen: Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Roche; Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Novartis; Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Pfizer; Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Lilly; Honoraria (self), Travel / Accommodation / Expenses: Accord Healthcare; Research grant / Funding (institution): AstraZeneca; Research grant / Funding (institution): Eisai. All other authors have declared no conflicts of interest.
Study Design
Retrospective analysis of prospectively collected data.
Objectives
Our goal was to assess radiographic characteristics associated with agreement and disagreement in treatment ...recommendation in thoracolumbar (TL) burst fractures.
Methods
A panel of 22 AO Spine Knowledge Forum Trauma experts reviewed 183 cases and were asked to: (1) classify the fracture; (2) assess degree of certainty of PLC disruption; (3) assess degree of comminution; and (4) make a treatment recommendation. Equipoise threshold used was 77% (77:23 distribution of uncertainty or 17 vs 5 experts). Two groups were created: consensus vs equipoise.
Results
Of the 183 cases reviewed, the experts reached full consensus in only 8 cases (4.4%). Eighty-one cases (44.3%) were included in the agreement group and 102 cases (55.7%) in the equipoise group. A3/A4 fractures were more common in the equipoise group (92.0% vs 83.7%, P < .001). The agreement group had higher degree of certainty of PLC disruption 35.8% (SD 34.2) vs 27.6 (SD 27.3), P < .001 and more common use of the M1 modifier (44.3% vs 38.3%, P < .001). Overall, the degree of comminution was slightly higher in the equipoise group 47.8 (SD 20.5) vs 45.7 (SD 23.4), P < .001.
Conclusions
The agreement group had a higher degree of certainty of PLC injury and more common use of M1 modifier (more type B fractures). The equipoise group had more A3/A4 type fractures. Future studies are required to identify the role of comminution in decision making as degree of comminution was slightly higher in the equipoise group.
Study Design
Reliability study utilizing 183 injury CT scans by 22 spine trauma experts with assessment of radiographic features, classification of injuries and treatment recommendations.
Objectives
...To assess the reliability of the AOSpine TL Injury Classification System (TLICS) including the categories within the classification and the M1 modifier.
Methods
Kappa and Intraclass correlation coefficients were produced. Associations of various imaging characteristics (comminution, PLC status) and treatment recommendations were analyzed through regression analysis. Multivariable logistic regression modeling was used for making predictive algorithms.
Results
Reliability of the AO Spine TLICS at differentiating A3 and A4 injuries (N = 71) (K = .466; 95% CI .458 – .474; P < .001) demonstrated moderate agreement. Similarly, the average intraclass correlation coefficient (ICC) amongst A3 and A4 injuries was excellent (ICC = .934; 95% CI .919 – .947; P < .001) and the ICC between individual measures was moderate (ICC = .403; 95% CI .351 – .461; P < .001). The overall agreement on the utilization of the M1 modifier amongst A3 and A4 injuries was fair (K = .161; 95% CI .151 – .171; P < .001). The ICC for PLC status in A3 and A4 injuries averaged across all measures was excellent (ICC = .936; 95% CI .922 – .949; P < .001). The M1 modifier suggests respondents are nearly 40% more confident that the PLC is injured amongst all injuries. The M1 modifier was employed at a higher frequency as injuries were classified higher in the classification system.
Conclusions
The reliability of surgeons differentiating between A3 and A4 injuries in the AOSpine TLICS is substantial and the utilization of the M1 modifier occurs more frequently with higher grades in the system.
Study Design
Prospective Observational Study.
Objective
To determine the alignment of the AO Spine Thoracolumbar Injury Classification system and treatment algorithm with contemporary surgical ...decision making.
Methods
183 cases of thoracolumbar burst fractures were reviewed by 22 AO Spine Knowledge Forum Trauma experts. These experienced clinicians classified the fracture morphology, integrity of the posterior ligamentous complex and degree of comminution. Management recommendations were collected.
Results
There was a statistically significant stepwise increase in rates of operative management with escalating category of injury (P < .001). An excellent correlation existed between recommended expert management and the actual treatment of each injury category: A0/A1/A2 (OR 1.09, 95% CI 0.70-1.69, P = .71), A3/4 (OR 1.62, 95% CI 0.98-2.66, P = .58) and B1/B2/C (1.00, 95% CI 0.87-1.14, P = .99). Thoracolumbar A4 fractures were more likely to be surgically stabilized than A3 fractures (68.2% vs 30.9%, P < .001). A modifier indicating indeterminate ligamentous injury increased the rate of operative management when comparing type B and C injuries to type A3/A4 injuries (OR 39.19, 95% CI 20.84-73.69, P < .01 vs OR 27.72, 95% CI 14.68-52.33, P < .01).
Conclusions
The AO Spine Thoracolumbar Injury Classification system introduces fracture morphology in a rational and hierarchical manner of escalating severity. Thoracolumbar A4 complete burst fractures were more likely to be operatively managed than A3 fractures. Flexion-distraction type B injuries and translational type C injuries were much more likely to have surgery recommended than type A fractures regardless of the M1 modifier. A suspected posterior ligamentous injury increased the likelihood of surgeons favoring surgical stabilization.
Study design
Predictive algorithm via decision tree
Objectives
Artificial intelligence (AI) remain an emerging field and have not previously been used to guide therapeutic decision making in ...thoracolumbar burst fractures. Building such models may reduce the variability in treatment recommendations. The goal of this study was to build a mathematical prediction rule based upon radiographic variables to guide treatment decisions.
Methods
Twenty-two surgeons from the AO Knowledge Forum Trauma reviewed 183 cases from the Spine TL A3/A4 prospective study (classification, degree of certainty of posterior ligamentous complex (PLC) injury, use of M1 modifier, degree of comminution, treatment recommendation). Reviewers’ regions were classified as Europe, North/South America and Asia. Classification and regression trees were used to create models that would predict the treatment recommendation based upon radiographic variables. We applied the decision tree model which accounts for the possibility of non-normal distributions of data. Cross-validation technique as used to validate the multivariable analyses.
Results
The accuracy of the model was excellent at 82.4%. Variables included in the algorithm were certainty of PLC injury (%), degree of comminution (%), the use of M1 modifier and geographical regions. The algorithm showed that if a patient has a certainty of PLC injury over 57.5%, then there is a 97.0% chance of receiving surgery. If certainty of PLC injury was low and comminution was above 37.5%, a patient had 74.2% chance of receiving surgery in Europe and Asia vs 22.7% chance in North/South America. Throughout the algorithm, the use of the M1 modifier increased the probability of receiving surgery by 21.4% on average.
Conclusion
This study presents a predictive analytic algorithm to guide decision-making in the treatment of thoracolumbar burst fractures without neurological deficits. PLC injury assessment over 57.5% was highly predictive of receiving surgery (97.0%). A high degree of comminution resulted in a higher chance of receiving surgery in Europe or Asia vs North/South America. Future studies could include clinical and other variables to enhance predictive ability or use machine learning for outcomes prediction in thoracolumbar burst fractures.
Study Design
This paper presents a description of a conceptual framework and methodology that is applicable to the manuscripts that comprise this focus issue.
Objectives
Our goal is to present a ...conceptual framework which is relied upon to better understand the processes through which surgeons make therapeutic decisions around how to treat thoracolumbar burst fractures (TL) fractures.
Methods
We will describe the methodology used in the AO Spine TL A3/4 Study prospective observational study and how the radiographs collected for this study were utilized to study the relationships between various variables that factor into surgeon decision making.
Results
With 22 expert spine trauma surgeons analyzing the acute CT scans of 183 patients with TL fractures we were able to perform pairwise analyses, look at reliability and correlations between responses and develop frequency tables, and regression models to assess the relationships and interactions between variables. We also used machine learning to develop decision trees.
Conclusions
This paper outlines the overall methodological elements that are common to the subsequent papers in this focus issue.
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