Predictive and prognostic markers from endoscopic ultrasound with biopsies during definitive chemoradiation therapy in esophageal squamous cell carcinoma

doi:10.21203/rs.3.rs-2086745/v1

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Research Article

Predictive and prognostic markers from endoscopic ultrasound with biopsies during definitive chemoradiation therapy in esophageal squamous cell carcinoma

https://doi.org/10.21203/rs.3.rs-2086745/v1

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Journal Publication

published 20 Jul, 2023

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Introduction:

Endoscopic ultrasound (EUS) may play a role in evaluating treatment response after definitive chemoradiation therapy (dCRT) for esophageal squamous cell carcinoma (ESCC). This study explored the prognostic markers of EUS with biopsies and developed two nomograms for survival prediction.

Methods

A total of 821 patients newly diagnosed with ESCC between January 2015 and December 2019 were reviewed. We investigated the prognostic value of the changes in tumor imaging characteristics and histopathological markers by an interim response evaluation, including presence of stenosis, ulceration, tumor length, tumor thickness, lumen involvement, and tumor remission. Independent prognostic factors of progression-free survival (PFS) and overall survival (OS) were determined using Cox regression analysis and further selected to build two nomogram models for survival prediction. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to respectively assess its discriminatory capacity, predictive accuracy, and clinical usefulness.

Results

A total of 155 patients were enrolled in this study and divided into the training (109 cases) and validation (46 cases) cohorts. Tumor length, residual tumor thickness, reduction in tumor thickness, lumen involvement, and excellent remission (ER) of spatial luminal involvement in ESCC (ER/SLI) differed significantly between responders and non-responders. For patients undergoing dCRT, TNM stage (P = 0.001, 0.002), tumor length (P = 0.013, 0.008), > 0.36 reduction in tumor thickness (P = 0.004, 0.004) and ER/SLI (P = 0.041, 0.031) were independent prognostic markers for both PFS and OS. Time-dependent ROC curves, calibration curves, and DCA indicated that the predicted survival rates of our two established nomogram models were highly accurate.

Conclusion

Our nomogram showed high accuracy in predicting PFS and OS for ESCC after dCRT. External validation and complementation of other biomarkers are needed in further studies.

chemoradiation

esophageal cancer

interim response

nomogram

endoscopic ultrasound

Definitive chemoradiation therapy (dCRT) is a superior alternative for patients with unresectable esophageal cancer (EC) or those unwilling to undergo operative management [1]. In China, the pathological type of EC is, in the majority, esophageal squamous cell carcinoma (ESCC), which is dramatically inconsistent with the adenocarcinomas in Western countries [2]. In all, 40–75% of patients with ESCC may develop local recurrence after dCRT, with an increased risk of poor survival [3]. It has been reported that the clinical outcomes of EC significantly correlate with the tumor response to dCRT. Patients with a complete response (CR) to dCRT appear to be more likely to develop long-term survival, while those with residual disease are recommended to continue with reinforced or salvage treatment [4]. As a result, patients with less sensitivity to treatment are recommended to receive 60 Gy as a definitive radiation dose to improve localized control, rather than the international recommended standard dose of 50 Gy [5–8]. It is essential to evaluate the tumor response to dCRT, especially at an early timepoint, to predict the prognosis of patients with ESCC and determine whether additional reinforced therapeutic strategies are required.

Numerous studies have been carried out to evaluate the essential role of endoscopic ultrasound (EUS) in staging primary EC and treating early-stage EC with minimal local involvement [9]. EUS evaluations have been suggested to play a role in predicting pathological CR in patients with EC after neoadjuvant chemoradiation therapy (nCRT), and tumor thickness was significantly correlated with tumor remission grade. To date, relatively few studies have investigated the potential role of EUS in assessing tumor treatment response and predicting the prognosis of patients with ESCC who receive dCRT [10, 11].

At our institution, patients who underwent dCRT and had not received treatment previously for EC were recommended to have an interim response evaluation. EUS with biopsies was conducted when the radiation dose reached 40 Gy. Additional information was obtained about the tumor response to dCRT, which would greatly help guide subsequent management and assess prognosis [12, 13].

The current study aimed to evaluate the role of interim response evaluation in predicting treatment response and patient survival for ESCC according to a comparison of the results of pre- and interim-treatment EUS-based measurements.

Patients and Treatments

Between January 1, 2015, and December 31, 2019, a cohort of 821 patients who underwent dCRT and had not received treatment previously for EC (stage I-IVA) at the Tianjin Medical University Cancer Institute and Hospital were enrolled. Only biopsy-confirmed squamous cell carcinoma with pre- and interim-treatment EUS measurements was eligible for inclusion (Supplementary Figure S1). The included patients were categorized into training and validation cohorts (7:3) according to the timing of treatment initiation. The TNM staging system proposed by the American Joint Committee on Cancer (8th edition) was used. In patients who received dCRT, radiotherapy was performed with conventional fractionation schedules (5 days/week, 1.8–2.0 Gy/daily fraction). The radiation dose ranged from 45.0 to 63.0 Gy, with a median dose of 54.0 Gy, in 30 fractions using intensity modulated radiotherapy (IMRT) with concomitant chemotherapy, mainly 4 to 6 cycles (docetaxel and cisplatin, weekly).

Treatment Evaluation

EUS examinations with biopsies were performed in patients with EC before dCRT treatment. When the radiation dose reached 40 Gy, usually four to five weeks into treatment, EUS with biopsies was repeated. At least three different sites of any suspicious lesions in the esophagus were considered for biopsies. Examination records were reviewed for the presence of stenosis, ulceration, tumor length, tumor thickness, lumen involvement, and tumor remission. Among them, the tumor length was the distance between the upper and lower edges of the esophageal tumor. The tumor thickness was measured in millimeters from the esophageal lumen to the outer tumor edge (Fig. 1A). In cases of an impassable esophagus, the maximum tumor thickness of the passable part was measured instead. Lumen involvement was defined as the proportion of spatial and circumferential tumors involving the esophageal lumen (Fig. 1A). Histopathological evaluation was based on a scoring system originally designed to evaluate microscopic response to chemoradiation therapy (CRT) in ESCC [12, 14, 15]. Tumor remission was classified into three grades, and details are given in Fig. 1B and Supplementary Table S1.

Follow-up

All patients were assessed clinically based on CT, esophagography, and ultrasonography of the neck and abdomen 1 month after dCRT, according to the Response Evaluation Criteria for Solid Tumors (RECIST 1.1) [16]. The above examinations were performed every 3 months for 1 year, every 6 months for the next 2 years, and annually thereafter. Overall survival (OS) was measured from the initiation of treatment to the date of death or the date of the last follow-up. Progression-free survival (PFS) was calculated from the initiation of treatment to the date of lesion progression, including the primary tumor, regional lymph nodes, and distant areas. Locoregional recurrence (LRR) was defined as the time from the initiation of therapy to the progression of the irradiated regions. Patients with a LRR ≥ 24 months were classified as the group of responders [17].

Statistical Analyses

Continuous variables were analyzed using t-tests, and categorical variables were tested using the chi-square test or the Fisher exact test. Age, tumor length, baseline tumor thickness, residual tumor thickness, and lumen involvement were grouped with the median value. The cutoff value of the reduction in tumor thickness was calculated by the Youden index. Survival curves were plotted by the Kaplan–Meier method and assessed using the log-rank test. Univariate and multivariate Cox regression analyses were performed to generate hazard ratios (HR) and 95% confidence intervals (CI), and to explore the prognostic variables for constructing nomograms. The “pec,” “rms,” and “ggDCA” packages of R were applied to generate time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) for validating the nomogram, respectively [18]. All statistical tests were 2-tailed. A P < 0.05 represented a significant value. All analyses and data visualization were performed in SPSS (Version 25.0) and the R programming language (version 4.0.5).

Patient Characteristics and Overall Treatment Response

A total of 155 patients were enrolled in this study, with a median age of 62 years (range, 44 to 82 years), and were divided into training (109 patients) and validation cohorts (46 patients). The median follow-up was 47.0 months (95% CI, 44.6 to 49.5 months) in the training cohort and 34.7 months (95% CI, 32.2 to 37.2 months) in the validation cohort. By December 2021, 49 patients (34 from the training cohort and 15 from the validation cohort) were still alive. Eighty-three(76.1%) patients in the training cohort experienced relapse, of which 44 (53.0%) suffered a local recurrence (LR), 31 (37.3%) suffered a regional recurrence (RR), and 22 (26.5%) suffered distant metastases (DMs). The training cohort’s 1-, 2-, and 3-year OS rates were 75.0%, 51.0%, and 37.8%, respectively. Forty-three (43.9%) patients were classified as active responders, and 55 (56.1%) patients as non-responders. In the validation cohort, a total of 36 (78.3%) patients developed a recurrence, of which 18 (50.0%) experienced a LR, 14 (38.9%) experienced a RR, and 13 (36.1%) experienced DMs. The validation cohort’s 1-, 2-, and 3-year OS rates were 70.0%, 41.3%, and 31.8%, respectively, with 16 (40.0%) and 24 (60.0%) patients being classified as responders and non-responders, respectively.

Interim Analysis

The presence of stenosis was observed in 42 (38.5%) of 109 patients in the training cohort and 21 (45.7%) of 46 patients in the validation cohort, respectively. As for ulceration, 20 (18.3%) of 109 patients and 10 (21.7%) of 46 patients were observed in the training and validation cohorts, respectively. In the training cohort, excellent remission (ER), good remission (GR), and minor remission (MR) were achieved by 59 (54.1%), 30 (27.5%), and 20 (18.3%) patients, respectively (Fig. 2A). In the validation cohort, the rates were 22 of 46 (47.8%) for ER, 14 of 46 (30.4%) for GR, and 10 of 46 (21.7%) for MR (Fig. 2B). The interim response evaluation revealed that, after CRT, tumor thickness was significantly reduced in the training cohort (14.9 ± 5.5 mm vs. 9.9 ± 3.6 mm, P < 0.001) (Fig. 2C) and also in the validation cohort (16.3 ± 6.5 mm vs. 10.1 ± 3.7 mm, P < 0.001) (Fig. 2D). However, no obvious changes of lumen involvement were observed during the treatment in these two cohorts (training cohort, 0.74 ± 0.23 vs. 0.72 ± 0.24, P = 0.152; validation cohort, 0.83 ± 0.20 vs. 0.80 ± 0.21, P = 0.384) (Figs. 2E, F).

Prognostic Significance Of The Interim Analysis

Clinical factors related to responders are shown in Table 1. A significant correlation was found between the interim response evaluation outcomes and responders. Residual tumor thickness (8.56 ± 3.15 vs. 11.13 ± 3.60mm, P < 0.001), reduction of tumor thickness (0.38 ± 0.17 vs. 0.26 ± 0.16, P < 0.001), tumor length (4.72 ± 2.25 vs. 5.66 ± 2.16cm, P = 0.037), and lumen involvement at baseline (0.70 ± 0.24 vs. 0.79 ± 0.22, P = 0.043) and during treatment (0.68 ± 0.23 vs. 0.77 vs. 0.23, P = 0.045) were significantly different between responders and non-responders (Table 1). No significant correlations were found for stenosis (P = 0.100), ulceration (P = 0.862), baseline tumor thickness (P = 0.323) and tumor remission (P = 0.082) (Table 1). Responders had a larger proportion of ER than non-responders; however, the p-value was not significant. We then combined tumor remission with spatial luminal involvement (SLI) during treatment; ER and SLI tumors achieved higher predictive values for responders, with a specificity of 83.6% (46/55, 95%CI 70.7–91.8%, P = 0.001) (Table 1).

Table 1

Clinical evaluation outcomes by EUS with biopsies of responders and non-responders^†
Variables	Responders (42)	Non-responders (56)	P
Stenosis			0.100
Yes	14	27
No	29	28
Ulceration			0.862
Yes	8	11
No	35	44
Tumor length (mm)	4.72 ± 2.25	5.66 ± 2.16	0.037
Tumor thickness (mm)
Baseline	14.37 ± 5.59	15.44 ± 4.99	0.323
Residual	8.56 ± 3.15	11.13 ± 3.60	< 0.001
Reduction	0.38 ± 0.17	0.26 ± 0.16	< 0.001
Lumen involvement
Baseline	0.70 ± 0.24	0.79 ± 0.22	0.043
Residual	0.68 ± 0.23	0.77 ± 0.23	0.045
Biopsies			0.082
Minor	5	14
Good	10	17
Excellent	28	24
Combination analysis			0.001
ER and SLI	20	9
Others	23	46
^†98 patients were included in the analysis of the training cohort; the remaining 11 patients were not included due to the short follow-up time. Abbreviations: ER, excellent remission; SLI, spatial luminal involvement.

Independent Prognostic Factors For Pfs And Os

Survival data for the primary cohort were analyzed. Patients with ER or SLI tended to have improved PFS and OS compared to those without, although the difference was not significant (PFS, P = 0.058, 0.086; OS, P = 0.11, 0.12). However, patients with both ER and SLI had significantly better PFS and OS than those with ER alone, SLI alone, or neither (PFS, P = 0.004; OS, P = 0.002) (Fig. 3). Table 2 shows the results of the univariate Cox regression analysis. Stenosis, baseline T, baseline N, TNM stage, tumor length, and reduction in tumor thickness were associated with PFS and OS. Residual tumor thickness was only associated with OS (P = 0.042), but not with PFS (P = 0.109). Variables with a p-value < 0.05 in the univariate analysis were selected for the multivariate Cox regression analysis. Since the TNM stage combines the depth of tumor infiltration and the status of lymph node metastasis, we only included the TNM stage for further analysis. Finally, TNM stage (P = 0.001, 0.002), tumor length (P = 0.013, 0.008), reduction in tumor thickness (P = 0.004, 0.004), and ER/SLI (P = 0.041, P = 0.031) were found to be independent prognostic factors for PFS and OS (Table 3).

Table 2

Patient and tumor characteristics and univariate Cox regression of variables associated with PFS and OS
Variables	N (%)	PFS		OS
Variables	N (%)	HR (95% CI)	P value	HR (95% CI)	P value
Age,median,y	62(44–82)	0.875(0.568–1.346)	0.543	1.042(0.662–1.642)	0.857
Male sex	90(82.6)	1.502(0.830–2.717)	0.178	1.366(0.735–2.536)	0.324
Smoke	79(72.5)	1.083(0.787–1.491)	0.625	0.998(0.694–1.437)	0.992
T1-3 vs T4	85(78.0)	1.822(1.099–3.022)	0.020	1.864(1.114–3.119)	0.018
N0-1 vs N2-3	71(65.1)	1.813(1.163–2.826)	0.009	2.005(1.262–3.186)	0.003
TNM category			0.002		0.003
I/II	23(21.1)	1.0		1.0
III	55(50.5)	1.758(0.958–3.225)	0.069	2.237(1.114–4.491)	0.024
IV	31(28.4)	3.156(1.643–6.064)	0.001	3.552(1.704–7.406)	0.001
Ulceration	20(18.3)	1.203(0.697–2.076)	0.507	1.172(0.654-2.100)	0.593
Stenosis	42(38.5)	1.594(1.029–2.467)	0.037	1.640(1.036–2.596)	0.035
Tumor length > 5.0 cm	50(45.9)	1.622(1.051–2.502)	0.029	1.769(1.122–2.789)	0.014
Tumor thickness (mm)
Baseline ≥ 15 mm	52(47.7)	0.999(0.649–1.538)	0.997	1.117(0.709–1.760)	0.633
Residual ≥ 10 mm	49(45.0)	1.426(0.924–2.201)	0.109	1.608(1.017–2.543)	0.042
Reduction ≥ 0.36	51(46.8)	0.557(0.359–0.865)	0.009	0.548(0.345–0.872)	0.011
Lumen involvement
Baseline ≥ 0.67	55(50.5)	1.307(0.848–2.013)	0.225	1.264(0.803–1.990)	0.312
Residual ≥ 0.67	51(46.8)	1.458(0.946–2.248)	0.088	1.437(0.909–2.273)	0.121
Tumor remission			0.123		0.230
Minor	20(18.3)	1.0		1.0
Good	30(27.5)	0.577(0.333-1.000)	0.050	0.616(0.344–1.103)	0.103
Excellent	59(54.1)	0.795(0.434–1.454)	0.456	0.829(0.440–1.563)	0.562
Combination analysis
ER and SLI	32(29.4)	1.0		1.0
others	77(70.6)	0.480(0.289–0.798)	0.005	0.428(0.245–0.748)	0.003
Abbreviations: PFS, progression free survival; OS, overall survival; HR, hazard ratios; CI, confidence intervals; ER, excellent remission; SLI, spatial luminal involvement.

Table 3

Multivariable Cox regression of variables associated with PFS and OS
Variables	PFS		OS
Variables	HR (95% CI)	P	HR (95% CI)	P
Stenosis	1.508(0.964–2.359)	0.072	1.528(0.948–2.463)	0.081
TNM category		0.001		0.002
I/II	1.0		1.0
III	1.124(0.596–2.121)	0.717	1.504(0.728–3.106)	0.271
IV	3.009(1.530–5.918)	0.001	3.588(1.646–7.821)	0.001
Tumor length	1.770(1.128–2.780)	0.013	1.903(1.185–3.057)	0.008
Tumor thickness
Residual > 10mm			0.838(0.478–1.470)	0.538
Reduction > 0.36	0.491(0.301-0.800)	0.004	0.456(0.265–0.782)	0.004
Others vs ER and SLI	0.576(0.339–0.977)	0.041	0.479(0.245–0.934)	0.031
Abbreviations: PFS, progression free survival; OS, overall survival; HR, hazard ratios; CI, confidence intervals; ER, excellent remission; SLI, spatial luminal involvement.

Development And Validation Of Nomograms

Using the four prognostic markers that were demonstrated to be significantly independent in the multivariate Cox regression analysis, we constructed two nomograms to predict the 1-, 2-, and 3-year PFS and OS for ESCC patients who received dCRT (Fig. 4A, 5A). The possibilities of PFS and OS at 1, 2 and 3 years were estimated by adding the points of each item on the nomogram.

We mainly evaluated the predictability of the nomograms from three aspects: discrimination, calibration, and clinical effectiveness. Our nomograms yielded a C-index of 0.713 (95% CI 0.663–0.762) in predicting PFS and 0.711 (95% CI 0.657–0.765) in predicting OS. Additionally, the time-dependent ROC curves of the nomograms demonstrated a better discrimination of PFS and OS than those of the TNM stage at almost all time points in the follow-up, in both the training (Figs. 4B, 5B) and validation cohorts (Figs. 4C, 5C). The calibration curves for 1-, 2-, and 3-year OS and PFS revealed an excellent agreement between the observed survival rates and the predictions of the nomograms, implying the superior accuracy of the predictions (Figs. 4D, E, 5D, E). Besides, diagrams of the DCA showed that the net benefits of our nomograms were significantly higher than those of the extreme curves, and more than those of the TNM stage in predicting PFS (Figs. 4F, G) and OS (Fig. 5F, G).

Risk stratification for PFS and OS

We summed up the prognostic scores of all independent risk markers in the nomogram models, and the total points ranged from 0–264 for PFS and from 0–273 for OS in the training cohort. Using the median value as a cutoff, we further separated patients into high- (PFS, ≥ 133.5; OS, ≥ 156.5) and low-risk (PFS, < 133.5; OS, < 156.5) groups. We found that the PFS and OS in both groups significantly differed (PFS, HR = 3.097, 95% CI 1.960–4.893, P < 0.001; OS, HR = 3.279, 95% CI 2.007–5.356, P < 0.001) (Fig. 6A, B), which was consistent with the results obtained in the validation group (PFS, HR = 4.977, 95% CI 2.247–11.025, P < 0.001; OS, HR = 5.719, 95% CI 2.356–13.886, P < 0.001) (Fig. 6C, D).

In the current study, we assessed both tumor imaging characteristics and histopathological performance by EUS with biopsies to capture the changes in tumor burden from the macro and micro perspectives, which indicated the response of tumors to dCRT. We found that reduction in tumor thickness, tumor length, ER/SLI, and TNM stage were significantly associated with local control and the survival probability of patients with ESCC. Furthermore, we established two visualized nomogram models combining these prognostic markers, which may enable clinicians to stratify prognostic subgroups and adapt the therapeutic schedule for patients with ESCC.

Most studies try to assess the early response of tumors to dCRT in patients with EC using magnetic resonance imaging (MRI), positron emission tomography with integrated computed tomography (PET/CT), or other imaging examinations. Quantitative imaging values, especially for classical MRI parameters, such as ADC values, differ between scanners and might not be standardized, as the values of ADC vary in different MRI devices [19, 20]. Another nonnegligible disadvantage is that MRI or PET/CT cannot discern the lesions confined to the mucosal layer [17]. Sakurada et al. combined high-resolution T2-weighted images with diffusion-weighted magnetic resonance imaging (DWI) for the detection of early EC, and only 33% of T1 carcinomas were detected accurately [21]. Subsequently, some other studies have highlighted the value of EUS in overcoming these limitations, which had become a standard measurement to identify tumor histological types and assist in tumor staging of patients with EC.

The predictive value of EUS has been confirmed in the nCRT field. A single-center retrospective study revealed that tumor thickness reduced by more than 50% after neoadjuvant therapy was significantly associated with tumor downgrade and long-term survival [22]. Another substudy of the preSANO trial did not find an association between tumor response and the reduction ratio of tumor thickness [11]. However, an absolute value of tumor thickness > 4.5 mm after completion of nCRT could predict residual disease with a sensitivity of 87%. In our present study, both residual thickness and changes in tumor thickness showed a significant correlation with active responders (Residual, P < 0.001; reduction in thickness, P < 0.001). However, survival analysis showed that only changes in tumor thickness were correlated with patient survival rates and were considered as an independent prognostic marker of PFS and OS. The possible causes for this discrepancy may be the difference in tumor histological types and the varied cutoff values of tumor thickness in different studies.

Compared with esophageal adenocarcinoma, posttreatment endoscopic biopsy played an improved role in predicting treatment response to CRT of ESCC. Qian et al. found that ER combined with tumor-infiltrating lymphocytes > 60% (LPE, lymphocyte-predominant ESCC) during CRT correlated with pCR and cancer-specific survival for patients with ESCC. During the interim response evaluation, patients evaluated with ER/LPE tended to have more improved survival rates compared with other patients who had ESCC [12]. Similar results were found in our present study, patients with ER or SLI were associated with a better PFS and OS in ESCC; however, the difference was not significant. When we combined both factors, patients with ER/SLI obtained significantly improved PFS (P = 0.004) and OS (P = 0.002) rates than other patients. We have also found a significant correlation between ER/SLI and responders. ER/SLI showed high predictive values for 2-year locoregional control, with a specificity of 83.6%. In other words, cases that did not achieve both ER and LIE during treatment tended to have locoregional failure after dCRT. This information obtained at the early timepoint of the treatment would have great importance in guiding subsequent management and assessing prognosis.

To our knowledge, our study is the first to assess EUS-based measurements pre- and interim-dCRT to evaluate the tumor response to dCRT in ESCC patients. Compared with the individual value before or during treatment, we believed that the reduction in tumor thickness was more significant in tumor assessment clinically for patients with ESCC who received dCRT, which was also consistent with the findings from other previous studies [22–25]. Using changes in tumor thickness appears superior for early tumor response evaluation compared to downgrading traditional EUS-based T staging [24, 26]. Another strength of this study was the relatively complete clinical data, including both tumor imaging characteristics and histopathological evaluation at baseline and during the treatment, which helped to assess the tumor response to dCRT comprehensively. In addition, at least three different sites of any suspicious lesions were considered for biopsies. Similar to bite-on-bite biopsies in the preSANO trial [10], a second biopsy sample was conducted at the same site, which helped detect residual tumors. Finally, we integrated the clinical parameters and pathological markers of tumors and established two visualized nomogram models with high accuracy in predicting PFS and OS.

Many studies have built prognostic models to predict the treatment response and survival probability of patients with EC who receive CRT [20, 27–29]. However, few studies have been specifically designed for squamous histology, whose clinicopathological features and biological behavior remarkably differ from adenocarcinoma. Only patients with ESCC who had complete clinical data and evaluation records were included in our study to ensure the reliability and accuracy of our nomograms. In addition, our nomograms are the first EUS-based models that are well-validated in another relatively independent cohort of patients with ESCC who were treated with dCRT. The selected prognostic markers in our nomograms were available to clinicians and easily applied to clinical practice. With great predictive performance in both the training cohort and validation cohorts, we believed that our models would have great potential to guide clinicians in assessing the overall treatment response and adapting therapy strategies of patients with ESCC. Low-risk cases may have satisfactory long-term survival, so close surveillance is recommended. However, other cases with poor treatment response may require a multidisciplinary approach, and a more intensive radiation dose is suggested.

We acknowledge the limitations of our analysis. In the interim response evaluation of 29 impassable esophagi, we measured the tumor thickness of the passable part, which may be less than the actual maximum tumor thickness, resulting in a limited influence on the results. Second, it is the genome that determines the sensitivity of esophageal cancer to CRT; from this point of view, our nomograms may not adequately assess the true response. A nomogram based on CD8, Foxp3, CD33, and PD-L1 yielded an AUC of 0.764 for 5-year OS prediction [30]. Other molecular biomarkers, such as ALDH1 and GLI1/HH, which have been reported to be associated with the therapeutic response [31], could be of complementary value to develop the current models. Finally, this was a retrospective single-institution analysis, and the performance of our models need to be validated in a larger external cohort.

Based on prognostic markers acquired from EUS with biopsies, we constructed and validated two individual nomograms to estimate PFS and OS in patients with ESCC who underwent dCRT. Before application in clinical practice, our current models must be validated and further refined, and their incorporation with other critical molecular biomarkers should also be further explored.

dCRT: Definitive chemoradiation therapy

EC: Esophageal cancer

ESCC: Esophageal squamous cell carcinoma

CR: Complete response

EUS: Endoscopic ultrasound

nCRT: Neoadjuvant chemoradiation therapy

CRT: Chemoradiation therapy

OS: Overall survival

PFS: Progression-free survival

LRR: Locoregional recurrence

HR: Hazard ratios

CI: Confidence intervals

ROC: Receiver operating characteristic()

DCA: Decision curve analysis

ER: Excellent remission,

GR: Good remission

MR: Minor remission

SLI: Spatial luminal involvement

MRI: Magnetic resonance imaging

PET/CT: Positron emission tomography with integrated computed tomography

DWI: Diffusion-weighted magnetic resonance imaging

LPE: Lymphocyte-predominant esophageal squamous cell carcinoma

Ethical Approval and Consent to Participate

The study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of Tianjin Medical University Cancer Institute and Hospital (approval number: bc2022102). The need for written informed consent was waived by the Tianjin Medical University Cancer Institute and Hospital Ethics Committee due to retrospective nature of the study.

Consent for Publication

Not applicable.

Conflicts of Interest

All authors have completed the ICMJE uniform disclosure form. The authors have no conflicts of interest to declare.

Acknowledgements

We would like to acknowledge the patients who participated in this study.

Funding

This work is supported by the National Natural Science Foundation of China (Grant No.82073348).

Contributions

PQ, CX, and WP conceptualized the study. DQ, WX, and ZK collected the patient data. PQ, CX, and WP contributed to data curation. CF and ZG analyzed and interpreted data. DQ and WX drafted the manuscript. ZW, PQ and CX revised the manuscript for critical intellectual content. All authors have seen and approved the final version of the manuscript.

Data Availability

The clinicopathological data used to support the findings of this study are available from the corresponding author upon request.

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No competing interests reported.

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Predictive and prognostic markers from endoscopic ultrasound with biopsies during definitive chemoradiation therapy in esophageal squamous cell carcinoma

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Abstract

Introduction:

Methods

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Conclusion

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Introduction

Materials And Methods

Patients and Treatments

Treatment Evaluation

Follow-up

Statistical Analyses

Results

Patient Characteristics and Overall Treatment Response

Interim Analysis

Prognostic Significance Of The Interim Analysis

Independent Prognostic Factors For Pfs And Os

Development And Validation Of Nomograms

Risk stratification for PFS and OS

Discussion

Conclusion

List Of Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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Version 1