Sage Journals: Discover world-class research

Abstract

Introduction: Neoadjuvant chemo-radiotherapy (nCRT) before surgery was a standard treatment strategy for locally advanced rectal cancer (LARC). The aim of this study was to assess the relationship between the predictive factors and pathological complete response (pCR) in rectal cancer patients, especially in ultra-low ones. Method: A total of 402 patients were involved in this retrospective study. The logistic regression analyses were used to compare the different subgroups in univariate analysis. Multivariate analysis was performed to determine the independent predictive factors of pCR by using a logistic regression model. Results: A total of 402 patients received preoperative CRT. In all patients, multivariate analysis revealed that circumferential tumor extent rate (CER) (≤ 2/3cycle vs >2/3 cycle, P < .001, OR = 4.834, 95% CI: 2.309-10.121), carcinoembryonic antigen (CEA) level (both ≤ 5 vs pre > 5 and post ≤ 5 vs both > 5, P = .033, OR = 1.537, 95% CI: 1.035-2.281), and interval time between the end of CRT and surgery (P = .031, OR = 2.412, 95% CI: 1.086-5.358) were predictive factors for pCR. The area under the curve (AUC) of the predictive model was 0.709 (95% CI: 0.649-0.769), which was significantly higher than the CER (0.646, 95% CI: 0.584-0.709), interval time (0.563, 95% CI: 0.495-0.631) and CEA level (0.586, 95% CI: 0.518-0.655). In ultra-low rectal patients, multivariate logistic regression analysis revealed that CER (≤ 2/3 cycle vs > 2/3 cycle, P = .003, OR = 7.203, 95% CI: 1.934-26.823) and mismatch repair (MMR) status (pMMR vs dMMR, P = .016, OR = 0.173, 95% CI: 0.041-0.720) were predictive factors for pCR. The AUC of the predictive model was 0.653 (95% CI: 0.474-0.832). Conclusion: New predictive models were varied by the histologic types and MMR statuses to evaluate the trend of tumor response to nCRT in all RC cases and ultra-low RC patients, which may be used to individualize stratify for selected LARC patients.

Keywords

rectal cancer ultra-low rectal cancer preoperative chemo-radiotherapy pCR predictive model

Introduction

Neoadjuvant chemoradiotherapy (nCRT), surgery, and adjuvant chemotherapy (CT) were standard treatment strategies for rectal cancers (RCs), especially locally advanced RCs.^1,2 The implementation of nCRT before surgery could downsize tumor stage, reduce local recurrence rates, and improve organ preservation and quality of life for patients with low-RC.

Ultra-low subtype was recognized as an independent poor prognostic factor for RC patients.³ The rate of sphincter preservation surgery for ultra-low RC was still < 50% due to high local recurrence and surgeon experience.⁴ Nowadays, tumoral response to neoadjuvant treatment has been proven as a key factor in transforming the mutilating radical surgery to a sphincter preservation approach.^5,6

In the GRECCAR prospective study,⁴ the circumferential resection margin (CRM) showed a strongly unfavorable prognosis for ultra-low RC, the 10-year survival rates with a CRM of below 1 mm was less than the CRM greater than or equal to 1 mm (P < .001, 22.2% vs 68.9%). The significant volumetric tumoral response after neoadjuvant therapy was associated with tumor-free CRM, which was clearly confirmed as an essential prognostic factor for operative strategy selection and long-term overall survival in this study.

Approximately 10% to 40% of patients achieved pathological complete response (pCR) after nCRT shown in several research which were confirmed by pathology and surgery.⁷ Although various retrospective analyses showed that an increased tumor response rate had a positive correlation with several clinical as well as pathologic factors such as T stage, MMR status, tumor location, interval time, or dose of radiotherapy, there were limited studies to assess the relationship between the predictive factors and pCR in ultra-low RC patients.

In view of the fact, that the tumor pathologic response was hard to assess before resection, it will benefit patients with RC to establish an effective predictive system to evaluate the tumor response, which would assist in offering more suitable clinical decisions for different patients. For example, ultra-low RC patients with pCR could adopt transanal endoscopic microsurgery (TEMS) or close observation to preserve sphincter function.

This study aims to determine the factors that provide independent predictive values of pCR for RC patients and ultra-low RC patients with neoadjuvant CRT (chemo-radiotherapy) and propose a clinical point score to evaluate the prediction of pCR for these patients.

Methods and Materials

Patient Selection

The inclusion criteria were as follows: RC patients confirmed by pathology with cT1-T4 and cN0-2 stage, who had accepted nCRT and surgery. Whereas patients with distant metastases or no surgery, as well as no detailed information on clinical characteristics and complete pathological information, were excluded.

The patients with RC were defined as 3 groups by the distance to the anal margin. They are a group of ultra-low (≤ 3 cm from the lower edge of the tumor to the anal margin), a group of low (between 3 and 5 cm), and a group of medium-high (between 5 and 10 cm and more than 10 cm).

Mismatch repair (MMR) status was defined by immunohistochemistry (IHC). Deficiency mismatch repair (dMMR) was defined as negative expression of human mutS homolog 6 (hMSH6), PMS2 genes, human mutL homolog 1 (hMLH1) or human mutS homolog 2 (hMSH2). Proficiency mismatch repair (pMMR) was defined as all the positive expressions of these 4 proteins. All resected specimens were assessed by 2 pathologists, and pCR was defined as the absence of any viable adenocarcinomatous cells in the resected sample using the American Joint Committee on Cancer (AJCC).⁷ Circumferential tumor extent rate (CER) was calculated by the formula: maximal diameter of tumor/maximal diameter of total inner circumference × 100⁸ (Figure 1).

Figure 1.

The graphical representation of CER in MRI.

A total of 402 patients were eligible from December 2015 to November 2020 at the Radiation Therapy Department, Changhai Hospital, Naval Military Medical University. The analyzed data included age, gender, cTNM stage (preoperative stage assessed by pelvis MRI), pathological information, MMR status, tumor location, interval time to surgery, type of radiotherapy, and system treatment records. The primary tumor pathological regression grade after nCRT was assessed by the Dworak regression scale.

Treatment Technique and Patients’ Follow-Up

All patients received neoadjuvant radiation therapy (RT) including a long-course treatment scheme of 40 to 50.4Gy delivered in 20 to 28 fractions over 4 to 6 weeks and short-course neoadjuvant RT (25-33 Gy delivered in 5-11 fractions). Neoadjuvant RT treatments with IMRT (intensity modulated radiation therapy) delivered by linear Accelerator (Varian Medical Systems, Palo Alto, CA), VMAT (Elekta Medical Systems, Synergy, VMAT), and PLDR (pulsed low dose rate radiotherapy).

Formulas and Statistical Analysis

The logistic regression analyses were used to compare the different subgroups in univariate analysis. Multivariate analysis was performed to determine the independent predictive factors of pCR by using a logistic regression model. A risk score was derived from the final multivariate model. Factors with a P-value < .05 in the univariate analysis were entered as candidate variables into a multivariate analysis.

After the logistic regression model, the regression coefficients were rounded to the nearest decimal to facilitate the calculation in order to be easily applied in clinical practice. The receiver operating characteristic (ROC) curve was plotted using the IBM SPSS and the area of difference under the ROC curve (AUC) is used to assess the performance of the predictive model. Statistical significance was set at P < .05. Statistical analyses were performed using IBM SPSS version 24.0 (SPSS Inc., Armonk, NY).

Results

The Patients’ Clinical, Treatment, and Histopathological Characteristics

A total of 404 RC patients confirmed with pathology, who had undergone preoperative nCRT between December 2015 and November 2020 were enrolled in this retrospective study. Two patients were excluded because of the discontinued treatment. Most patients were male (292 cases, 72.6%) and the median age was 59 years (range: 24-81). All patients had Eastern Cooperative Oncology Group (ECOG) 0-1. 116 (28.9%) patients had a smoking history and 69 (17.2%) patients had a drinking history. Tumor staging was performed according to the eighth edition of the AJCC TNM classification. A total of 21 patients were classified as clinical stage I (cT1N0, cT2N0), 44 patients were classified as clinical stage II (cT3N0, cT4N0) while 337 patients were classified as stage III (cT1-4N1, cT1-4N2). The median distance of the tumor to the anal verge was 4 cm (range: 0-11 cm). The median length of the tumor was 4 cm (range: 1.3-12 cm), the median tumor thickness was 1 cm (range: 0.4-4 cm) and the median circumferential extent rate was 2/3 cycle (range: 1/4-one cycle). The median interval between the end of CRT and surgery was 8 weeks. The median CEA levels before and after preoperative CRT were 4.62 ng/mL (range: 0.64-675.72 ng/mL) and 2.59 ng/mL (range: 0.5-270.50 ng/mL), respectively. Similarly, the carbohydrate antigen (CA199) values before and after preoperative CRT were 14.19 U/mL (range: 2.17 -> 1200 U/mL) and 7.89 U/mL (range: 1.22 -> 1200 U/mL), respectively (Table 1).

Table 1.

Patients’ Clinical, Treatment, and Histopathological Characteristics.

Characteristics	No./median (range)	Proportion (%)
Patient characteristics
Sex
Male	292	72.6%
Female	110	27.4%
Age (years)	59 (24-81)
Smoke
Yes	116	28.9%
No	286	71.1%
Drink
Yes	69	17.2%
No	333	82.8%
Disease characteristics
T stage
cT1	1	0.2%
cT2	63	15.7%
cT3	310	77.1%
cT4	28	7%
N stage
cN0	63	15.7%
cN1	172	42.8%
cN2	167	41.5%
TNM stage
I	21	5.2%
II	44	11%
III	337	83.8%
Distance from the anal verge (cm)
≤ 3	135	33.6%
3-5	156	38.8%
> 5	111	27.6%
Tumor length (cm)	4 (1.3-12)
Tumor thickness (cm)	1 (0.4-4)
Circumferential tumor extent rate (CER)	2/3 (1/4-1)
Hemoglobin
≥ 120 g/L	330	82.1%
< 120 g/L	72	17.9%
CEA pre- and post-CRT (ng/mL)
Both > 5	66	16.4%
Pre > 5 and post ≤ 5	110	27.4%
Both ≤ 5	226	56.2%
CA199 pre- and post-CRT (U/mL)
Both > 5	17	4.2%
Pre > 5 and post ≤ 5	64	15.9%
Both ≤ 5	321	79.9%
Treatment characteristics
Neoadjuvant treatment
Single agent (5-Fu/LV or Capecitabine)	26	6.5%
Double agent (FOLFOX/CAPEOX)	300	74.6%
None	76	18.9%
Synchronous chemotherapy
Yes	372	92.5%
No	30	7.5%
RT course
Long	379	94.3%
Short	23	5.7%
RT technology
VMAT	334	83.1%
IMRT	61	15.2%
PLDR	7	1.7%
Radiotherapy dose (Gy)	50 Gy (25-50.4)
Interval
≥ 8 weeks	318	79.1%
< 8 weeks	84	20.9%
Pathological characteristics
TRG
0	75	18.7%
1	82	20.3%
2	178	44.3%
3	67	16.7%
Mismatch repair status
dMMR	51	12.7%
pMMR	263	65.4%
Unknown	88	21.9%
Histological type (%)
Well	19	4.7%
Moderate	282	70.2%
Poor/undifferentiated	42	10.4%
Unknown	59	14.7%
Ki-67 status
≥ 30%	243	60.4%
< 30%	75	18.7%
Unknown	84	20.9%
CAM5.2 status
(+)	256	63.7%
(−)	13	3.2%
Unknown	133	33.1%
Topo II status
> 25%	190	47.3%
≤ 25%	124	30.8%
Unknown	88	21.9%
P53 status
(+)	195	48.5%
(−)	119	29.6%
Unknown	88	21.9%
Kras status
Mutation	106	26.3%
Wild	147	36.6%
Unknown	149	37.1%

Abbreviations: CEA, carcinoembryonic antigen; CER, circumferential tumor extent rate; MMR, mismatch repair; RT, radiotherapy; VAMT, Volumetric Modulated Arc Therapy; IMRT, intensity modulated radiation therapy; PLDR, pulsed low dose rate radiotherapy; TRG, tumor regression grade.

A total of 372 patients received concomitant CT: 5-Fu and leucovorin or capecitabine in 344 patients and with the addition of oxaliplatin in 28 patients. Besides that, in all 402 patients, 326 patients received neoadjuvant CT, which consisted of 5-FU/LV or capecitabine alone in 26 patients and FOLFOX/CAPEOX in 300 patients. According to the NCCN guidelines (version 3.2022), patients not receiving standard neoadjuvant CT were excluded. A total of 379 patients were treated with long-course RT with a total radiation dose of 50 to 50.4 Gy delivered in 25 to 28 fractions over 5 weeks, whereas 23 patients with short-course RT were carried out with a total dose of 25 Gy delivered in 5 fractions in 1 week. The median interval between CRT and surgery was 8 weeks.

Response to nCRT

A total of 402 patients were included, among which 75 (18.66%) patients had pCR after surgery. When histological types were assessed, 301 (74.9%) patients were found to be well/moderately differentiated and 42 (10.4%) patients were poor/undifferentiated. Tumor regression was graded (TRG) from 0 to 3. Among 402 patients, 75 (18.7%) patients had a complete response to CRT (TRG 0), and 260 patients (64.6%) had a good response (TRG 1 or 2). Poor response was observed in 67(16.7%) patients (TRG 3).

Predictive Model of pCR for RC Patients

Based on univariate analysis, pCR was associated with CER (P < .001), CEA level before and after CRT (P = .032), and the interval between the end of CRT and surgery (P = .016). For the analysis of histopathological characteristics, pCR might be associated with histological type (P < .001), cytokeratin 5.2 (CAM5.2) status (P < .001), and TOPO II status (P = .048) (Table 2). Multivariate logistic regression analysis revealed that CER (≤ 2/3 cycle vs > 2/3 cycle, P < .001, OR = 4.834, 95% CI: 2.309-10.121), CEA level (both ≤ 5 vs pre > 5 and post ≤ 5 vs both > 5, P = .033, OR = 1.537, 95% CI: 1.035-2.281), and the interval between the end of CRT and surgery (P = .031, OR = 2.412, 95% CI: 1.086-5.358) were predictive factors for pCR (Table 3). The point values of the predictors were assigned by the regression coefficients and were rounded to the nearest decimal for easy calculation (Table 4).

Table 2.

Univariate Analysis of Predictors Associated With pCR.

Characteristics	pCR	Non-pCR	P value^a
Sex
Male	51	241	.318
Female	24	86
Age (years)
≤ 59	43	177	.615
> 59	32	150
Smoke
Yes	15	101	.061
No	60	226
Drink
Yes	11	58	.525
No	64	269
T stage			.311
cT1-2	16	48
cT3	53	257
cT4	6	22
N stage			.529
cN0	12	51
cN1	36	136
cN2	27	140
TNM stage			.502
I	3	18
II	10	34
III	62	275
Distance from the anal verge (cm)			.294
≤ 3	30	105
3-5	29	127
> 5	16	95
Tumor length (cm)
≤ 4	37	195	.103
> 4	38	132
Tumor thickness (cm)
≤ 1	51	210	.536
> 1	24	117
Circumferential tumor extent rate (CER)
≤ 2/3	66	192	<. 001
> 2/3	9	135
Hemoglobin
≥ 120 g/L	62	268	.885
< 120 g/L	13	59
CEA pre- and post-CRT (ng/mL)			. 032
Both > 5	7	59
Pre > 5 and post ≤ 5	16	94
Both ≤ 5	52	174
CA199 pre- and post-CRT (U/mL)			.572
Both > 5	2	15
pre > 5 and post ≤ 5	10	54
Both ≤ 5	63	258
Neoadjuvant treatment			.097
Single agent	2	24
Double agent	63	237
None	10	66
Synchronous chemotherapy
Yes	70	302	.771
No	5	25
RT course
Long	74	305	.070
Short	1	22
Interval
≥ 8 weeks	67	251	. 016
< 8 weeks	8	76
Mismatch repair status
dMMR	6	45	.495
pMMR	23	240
Unknown	–	–

Histological type (%)
Well	4	15	<. 001
Moderate	14	268
Poor/undifferentiated	10	32
Unknown	–	–
Ki-67 status
≥ 30%	23	220	.693
< 30%	6	69
Unknown	–	–
CAM5.2 status
(−)	4	9	<. 001
(+)	6	250
Unknown	–	–
Topo II status
> 25%	3	175	.048
≤ 25%	7	111
Unknown	–	–
P53 status
(+)	15	180	.227
(−)	14	105
Unknown	–	–
Kras status
Mutation	2	104	.741
Wild	2	145
Unknown	–	–

Abbreviations: pCR, pathological complete response; CRT, chemoradiotherapy; CER, circumferential tumor extent rate; RT: radiotherapy; dMMR, deficiency mismatch repair; pMMR, proficiency mismatch repair.

^a Univariable analysis with logistic regression; bold values: P < .05.

Table 3.

Multivariate Analysis of Predictors Associated With pCR.

Variable	OR	95% CI	P value^a
Circumferential tumor extent rate (CER)	4.834	2.309-10.121	<.001
CEA	1.537	1.035-2.281	.033
Interval	2.412	1.086-5.358	.031

^a Multivariate analysis using the logistic regression; CI, confidence interval; bold values: P < .05.

Abbreviations: pCR, pathological complete response; CEA, carcinoembryonic antigen.

Table 4.

Calculation of the Predictive Model Score.

Variable		Regression coefficient	Score (points)
Circumferential tumor extent rate (CER)	≤ 2/3	1.58	2
Circumferential tumor extent rate (CER)	> 2/3		0
CEA pre- and post-CRT	Both ≤ 5		1
	pre > 5 and post ≤ 5	0.43	0.5
	Both > 5		0
Interval	≥ 8 W	0.88	1
Interval	< 8 W		0

Abbreviations: CRT, chemoradiotherapy; CER, circumferential tumor extent rate.

The total score for the 3 predictive factors could thus range from 0 to 4. The median score of the prognostic factors score in all patients was 3.0 points. If the scores were divided into 2 groups, patients with scores of 3 to 4 showed a higher rate of pCR than those with scores of 0 to 2 (27% vs 6.7%, P < .001). The sensitivity was 85.3% (64/75) with 47.1% (173/327) for specificity, 27% (64/237) for positive predictive value, 93.3% (154/165) for negative predictive value, and 54.2% (218/402) for overall accuracy. Furthermore, if the scores were divided into 2 groups, 0 to 3 versus 3.5 to 4, only 20 of the 75 patients with a score of 0 to 3 achieved a pCR, whereas 55 patients with scores of 3.5 to 4 achieved a pCR (30.6% vs 9.1%, P < .001). The sensitivity was 73.3% (55/75) with 61.8% (202/327) for specificity, 30.6% (55/180) for positive predictive value, 91.0% (202/222) for negative predictive value, and 63.9% (257/402) for overall accuracy (Table 5). The AUC of the predictive model was 0.709 (95% CI: 0.649-0.769), which was significantly higher than the 3 clinical factors, circumferential tumor extent rate (CER) (0.646, 95% CI: 0.584-0.709), interval time (0.563, 95% CI: 0.495-0.631) and CEA level (0.586, 95% CI: 0.518-0.655) (Figure 2). In addition, the variance inflation factor (VIF) of the 3 predictive factors were 1.017, 1.015, and 1.003, respectively. Tenfold cross-validation (mean AUC = 0.989) further demonstrated the reliability and high predictive value of the nomogram.

Figure 2.

The area under the curve (AUC) of the prognostic model in all rectal cancer patients.

Table 5.

The Predictive Model for Assessment of pathological complete response (pCR).

		pCR
		Yes (n = 75)	No (n = 327)
Score 1	0-2.5	11	154
	3-4	64	173
		Sensitivity (%)	85.3
		Specificity (%)	47.1
		Positive predictive value (%)	27.0
		Negative predictive value (%)	93.3
		Overall accuracy (%)	54.2
Score 2	0-3	20	202
	3.5-4	55	125
		Sensitivity (%)	73.3
		Specificity (%)	61.8
		Positive predictive value (%)	30.6
		Negative predictive value (%)	91.0
		Overall accuracy (%)	63.9

Ultra-Low RC Patients

A total of 135 patients of ultra-low RC were further analyzed. Based on univariate analysis, pCR was associated with CER (P = .012), CEA level before and after CRT (P = .032), and hemoglobin before CRT (P = .047). For the analysis of histopathological characteristics, pCR may be associated with mismatch repair status (P = .008) and CAM5.2 status (P < .001) (Table 6). Multivariate logistic regression analysis revealed that both CER (≤ 2/3 cycle vs > 2/3 cycle, P = .003, OR = 7.203, 95% CI: 1.934-26.823) and MMR status (pMMR vs dMMR, P = .016, OR = 0.173, 95% CI: 0.041-0.720) were predictive factors for pCR (Table 7). The point values of the predictors were assigned by the regression coefficients and were rounded to the nearest decimal to facilitate the calculation in ultra-low RC patients (Table 8). The AUC of the predictive model was 0.653 (95% CI: 0.474-0.832) (Figure 3) and the predicted efficiency was decreased in a way.

Figure 3.

The area under the curve (AUC) of the prognostic model in ultra-low rectal cancer patients.

Table 6.

Univariate Analysis of Predictors Associated With pCR in Ultra-Low Patients.

Characteristics	pCR	Non-pCR	P value^a
Sex
Male	18	64	.925
Female	12	41
Age (years)
≤ 57	16	64	.854
> 57	14	51
Smoke
Yes	15	101	.349
No	60	226
Drink
Yes	11	58	.124
No	64	269
T stage			.125
cT1-2	16	48
cT3	53	257
cT4	6	22
N stage
cN0	12	51
cN1	36	136
cN2	27	140	.423
TNM stage			.797
I	3	18
II	10	34
III	62	268
IV	0	7
Tumor length (cm)
≤ 3.5	14	60	.309
> 3.5	16	45
Tumor thickness (cm)
≤ 1	22	68	.380
> 1	8	37
Circumferential tumor extent rate (CER)
≤ 2/3	27	70	. 012
>2/3	3	35
Hemoglobin
≥ 120 g/L	28	81	. 047
< 120 g/L	2	24
CEA pre- and post-CRT (ng/mL)			.032
Both > 5	4	15
Pre > 5 and post ≤ 5	3	35
Both ≤ 5	23	55
CA199 pre- and post-CRT (U/mL)			.450
Both > 5	0	3
Pre > 5 and post ≤ 5	6	14
Both ≤ 5	24	88
Neoadjuvant treatment			.621
Single agent	1	9
Double agent	23	75
None	6	21
Synchronous chemotherapy
Yes	30	99	.180
No	0	6
RT course
Long	29	103	.892
Short	1	3
Interval
≥ 8 weeks	25	84	.145
< 8 weeks	5	21
Mismatch repair status
dMMR	4	8	. 008
pMMR	7	81
Unknown	–	–
Histological type (%)
Well	2	3	. 008
Moderate	6	86
Poor/undifferentiated	4	12
Unknown	–	–
Ki-67 status
≥30%	23	220	.693
<30%	6	69
Unknown	–	–
CAM5.2 status
(−)	2	1	<. 001
(+)	1	81
Unknown	–	–
Topo II status
> 25%	7	56	.963
≤ 25%	4	33
Unknown	–	–
P53 status
(+)	5	56	.263
(−)	6	33
Unknown	–	–
Kras status
Mutation	0	36	.174
Wild	2	38
Unknown	–	–

^a Univariable analysis with logistic regression; bold values: P < .05.

Table 7.

Multivariate Analysis of Predictors Associated With pCR in Ultra-Low Patients.

Variable	OR	95% CI	P value^a
Circumferential tumor extent rate (CER)	7.203	1.934-26.823	.003
MMR	0.173	0.041-0.720	.016

Abbreviations: pCR, pathological complete response; MMR: mismatch repair.

^a Multivariate analysis using the logistic regression; CI, confidence interval; bold values: P < .05.

Table 8.

Calculation of the Predictive Model Score in Ultra-Low Patients.

Variable		Regression coefficient	Score (points)
Circumferential tumor extent rate (CER)	≤ 2/3	1.975	2
	> 2/3		0
MMR	dMMR	1.754	2
	pMMR		0

Abbreviations: MMR: mismatch repair; dMMR, deficiency mismatch repair; pMMR, proficiency mismatch repair.

Discussion

The role of pCR as a prognostic factor for RC patients has been widely reported in the last decades,^9–13 and an average pCR rate of 22% (range 10%-30%) was observed in LARC patients with CRT before surgery. A review of 7 prospective studies including 2165 RC cases showed that the patients who received total neoadjuvant therapy (TNT) were associated with higher pCR rates of 29.9% compared with standard CRT of 14.9%.¹⁴

Although the relationship between the OS and pCR was controversial in several studies, RC patients with pCR had a significant survival benefit, lower local relapse, and fewer metastases compared to non-pCR patients. In a meta-analysis of 16 studies,¹⁵ complete responders had a 75% reduced risk of distant metastases and local recurrence rates compared with those nonresponders.

A long-term study demonstrated a 95% of 5-year overall survival rate and a 92% of 5-year disease-free survival for pCR patients, 77% of whom achieved a longer OS exceeding 10 years before the end date of the study.¹⁶

In our study, the pCR rate was 18.66% (75/402) in all enrolled patients and 22.22% in patients with ultra-low RCs (30/135). Achieving pCR was even more important for organ preservation in patients with ultra-low RCs. According to the limited prospective evidence, there was insufficient evidence to substantiate that the clinical and pathology factors are associated with pCR to CRT in ultra-low RC. Therefore, patients with ultra-low RC were further analyzed in our study.

In recent studies,^17–21 clinical characteristics of cTNM stage, tumor size, tumor location, the interval between neoadjuvant therapy and surgery, pathological factors of tumor differentiation, and mucinous histopathology were widely investigated to predict tumor response to CRT for RC. Moreover, the new predicting models of molecular biomarkers such as p53, p21, Ki-67, and epidermal growth factor receptor (EGFR) have been proven to be correlated with pCR for LARC, which strengthens the predicting efficacy of tumor response for preoperative CRT.²² A genotype of PGS-LARC model²³ comprised of 15 genes for predicting pCR had been established with whole exome sequencing, which was superior to other clinical features on the sensitivity and specificity of pCR prediction.

The 402 RC tumor samples had been allocated in the training cohorts, and constructed new predictive models comprising clinical and pathological factors for pCR prediction after nCRT, with satisfactory AUC, accuracy, sensitivity, and specificity. The AUCs of the new models in the training cohorts were 70.9% and 65.3%, which were all higher than the respective clinical factors (CER, interval time, CEA level and CER, mismatch repair status) in AUC, accuracy, sensitivity, and specificity for all RC and ultra-low RC cases, respectively. The clinical implication of this study is that it could provide probability for clinical decision-making in formulating a more personalized treatment strategy.

Serum carcinoembryonic antigen (CEA) was widely used as a biomarker for the diagnosis, assessment of treatment efficacy, and prognosis prediction of colo-RC. Several studies have shown that the pre-CRT serum level of CEA ≤ 5 ng/mL was related to pCR and positive tumor regression.^24–28 Cheong et al²⁹ demonstrated that both pre- and post-CRT CEA levels < 5 ng/mL and the change of CEA levels were associated with pCR (P < .001) and good response (OR = 5.07; 95% CI: 1.92-14.83, P = .002). Therefore, in our study, we evaluated the serum CEA levels of both pre- and post-CRT. The median CEA values before and after preoperative CRT were 4.62 ng/mL (range: 0.64-675.72 ng/mL) and 2.59 ng/mL (range: 0.5-270.50 ng/mL), respectively. We also analyzed the relationship between serum CEA and treatment response to CRT. Multivariate logistic regression analysis revealed that CEA level (both ≤ 5 vs pre > 5 and post ≤ 5 vs both > 5, P = .033, OR = 1.537, 95% CI: 1.035-2.281) was a predictive factor for pCR on the treatment response to CRT in patients with LARC.

The most commonly reported clinical factors related to pCR included cTNM stage, tumor size, circumferential extent rate (CER), and the tumor distance to the anal margin. It was also observed in our study that CER less than 2/3 was a predictor of pCR in univariate analysis (P < .001). A limited circumferential extent rate of less than 50% or 60% was considered as a significant predictor for patients with pCR in several studies.^30,31 CER had a positive correlation with tumor size, tumor invasion depth, nodal involvement, and TNM stage.⁸ Although there was no relationship between cTNM stage and pCR in our study, CER was easy to evaluate by MRI imaging as an independent predictor with pCR preoperative CRT.

There is sufficient evidence to demonstrate that the longer interval between neoadjuvant and surgery is not associated with an increased cumulative rate of pCR.^32–34 A phase III randomized trial showed that the delayed surgery interval of 11 weeks did not increase the rate of pCR after surgical resection compared to the 7-week group. Moreover, a longer interval may be associated with higher morbidity and more challenged mesorectal excision.³⁵

A recent meta-analysis³⁶ including 7 randomized trials showed a positive trend of pCR percentage over the weeks of interval before surgery was established until 16 weeks, which suggests that at least 10 weeks should be considered to achieve 95% of pCR cases. In our study, the relationship between interval and response to CRT was evaluated. Multivariate logistic regression analysis revealed that an interval of ≥ 8 weeks before surgery (P = .031, OR = 2.412, 95% CI: 1.086-5.358) was a predictive factor for pCR on the treatment response to CRT in patients with LARC.

A total of 33.6% (135/402) patients with ultra-low RC had achieved 22.22% pCR, which is better than the overall pCR rate of 18.66% (75/402) in our study. Das et al³⁰ analyzed 562 RC patients and found that lower tumor distance to the anal verge was a significant predictor of greater rates of pCR and downstaging.

The analysis of pCR in ultra-low RC patients was rarely reported in previous studies as an independent cohort. Univariate analysis revealed that both tumor circumferential extent rate (CER) (P = .003) and MMR status (P = .016) were independent predictors for pCR in patients of ultra-low RC in our study. Microsatellite instability (MSI) is a genome phenotypic abnormality that shows the defects in mismatch repair (MMR) system, in meanwhile, MSI exists in 15% of colorectal patients.³⁷ RC patients with MSI-high (MSI-H)/dMMR had been reported as a positive prognostic factor compared to MSI-low (MSI-L), microsatellite stability (MSS) or pMMR in several studies.^38,39 On the other hand, both pMMR and MSS were found to be significantly related to pCR in RC patients who accepted nCRT.⁴⁰ The relationship between pCR and MMR or MSI status in RC is still contradictory. MMR status had not been found to correlate with pCR for all cases in our study, while dMMR was found to have higher expression in the complete response group for ultra-low RC.

Some prospective trials supported that nearly 40% of colorectal cancers with dMMR responded to immunotherapy of the programmed death-1 (PD-1) blocker.⁴¹ Now the immunotherapy combined with conventional CT was under investigation to prove its effectiveness in metastatic colorectal cancer with dMM.² Many clinical trials were designed to evaluate the effectiveness of immunotherapy in the neoadjuvant setting for dMMR RCs. To our knowledge, this is the first study of the pCR predictive model in ultra-low RC after nCRT. Mismatch repair (MMR) status was found as a predictive factor for pCR in ultra-low rectal patients. These outcomes may provide significant evidence in increasing pCR rate, preserving organ function, and designing to evaluate the effectiveness of immunotherapy in the neoadjuvant setting for ultra-low RC in future prospective studies. Moreover, the watch and wait strategies for different groups of patients with RC could be classified with reference.

The combination of clinical features, pathological characteristics, imaging information features, molecular markers, and gene expression profiling could predict the efficacy of neoadjuvant therapy more accurately and guide the individualized clinical strategies for RC patients.

We proposed a new prediction model including clinical features, pathological characteristics, imaging information features, and molecular markers for different groups of RC patients. It will be beneficial for RC patients to evaluate the tumor response to nCRT with such an established effective predictive system.

The clinical significance of the predictive model was to facilitate the calculation and provide a new predictive system for ultra-low RC. Whereas some limitations in our study to establish the system. Firstly, it was a retrospective study in a single institution. Secondly, the incomplete pathological information for partial pCR patients before treatment may cause statistical bias. Lastly, large patient samples as well as longer follow-ups were needed. The applicability warrants prospective study for further validation.

Conclusion

In conclusion, we developed a prediction model to evaluate the trend of tumor response to nCRT for both RC patients and ultra-low RC patients.

Footnotes

Abbreviations

Acknowledgments

None.

Authors’ Contributions

SQ, LG, and TD have made equal contributions to the study and drafted the manuscript. XY made contribution to the statistical analysis. ZK made contributions to data collection. ZHJ is the principal investigator (PI) of this study and made contributions to the study design.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

This retrospective study obtained approval from the independent Ethics Committee of Changhai Hospital on August 30, 2019, The ethics number is CHEC2019-123 and all patients had signed informed consents.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Ministry of Science and Technology of China (2022YFC2503701, FW-ZXKT2022102502004), Shanghai Health Commission Leading Talent Program (2022LJ019), National Natural Science Foundation of China (82272742), Changhai Hospital Guhai Program (GH145-33) and Youth Starup Fund (2020QNB09).

ORCID iD

Huo-jun Zhang MD, PhD

References

Glynne-Jones

Wyrwicz

Tiret

, et al. Rectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2017;28(suppl_4):iv22-iv40. doi:10.1093/annonc/mdx224

Benson

Venook

Al-Hawary

, et al. Rectal cancer, version 2.2018, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2018;16(7):874-901. doi:10.6004/jnccn.2018.0061

Kim

Yeom

Kwak

, et al. Clinical outcomes of patients with locally advanced rectal cancer with persistent circumferential resection margin invasion after preoperative chemoradiotherapy. Ann Coloproctol. 2019;35(2):72-82. doi:10.3393/ac.2019.04.22

Rouanet

Rivoire

Gourgou

, et al. Sphincter-saving surgery after neoadjuvant therapy for ultra-low rectal cancer where abdominoperineal resection was indicated: 10-year results of the GRECCAR 1 trial. Br J Surg. 2021;108(1):10-13. doi:10.1093/bjs/znaa010

Weiser

Quah

Shia

, et al. Sphincter preservation in low rectal cancer is facilitated by preoperative chemoradiation and intersphincteric dissection. Ann Surg. 2009;249(2):236-242. doi:10.1097/SLA.0b013e318195e17c

Han

Choi

, et al. Clinical impact of tumor volume reduction in rectal cancer following preoperative chemoradiation. Diagn Interv Imaging. 2016;97(9):843-850. doi:10.1016/j.diii.2016.05.004

Chawla

Katz

Rauh

Monson

. Can surgery be avoided after preoperative chemoradiation for rectal cancer in the era of organ preservation? Current review of literature. Am J Clin Oncol. 2015;38(5):534-540. doi:10.1097/COC.0000000000000122

Tsurumaru

Takatsu

Kai

Oki

Ishigami

. Measurement of circumferential tumor extent of colorectal cancer on CT colonography: relation to clinicopathological features and patient prognosis after surgery. Jpn J Radiol. 2021;39(10):966-972. doi:10.1007/s11604-021-01141-5

Capirci

Valentini

Cionini

, et al. Prognostic value of pathologic complete response after neoadjuvant therapy in locally advanced rectal cancer: long-term analysis of 566 ypCR patients. Int J Radiat Oncol Biol Phys. 2008;72(1):99-107. doi:10.1016/j.ijrobp.2007.12.019

10.

Maas

Nelemans

Valentini

, et al. Long-term outcome in patients with a pathological complete response after chemoradiation for rectal cancer: a pooled analysis of individual patient data. Lancet Oncol. 2010;11(9):835-844. doi:10.1016/S1470-2045(10)70172-8

11.

Ortholan

Romestaing

Chapet

Gerard

. Correlation in rectal cancer between clinical tumor response after neoadjuvant radiotherapy and sphincter or organ preservation: 10-year results of the Lyon R 96-02 randomized trial. Int J Radiat Oncol Biol Phys. 2012;83(2):e165-e171. doi:10.1016/j.ijrobp.2011.12.002

12.

Valentini

van Stiphout

Lammering

, et al. Nomograms for predicting local recurrence, distant metastases, and overall survival for patients with locally advanced rectal cancer on the basis of European randomized clinical trials. J Clin Oncol. 2011;29(23):3163-3172. doi:10.1200/JCO.2010.33.1595

13.

Zorcolo

Rosman

Restivo

, et al. Complete pathologic response after combined modality treatment for rectal cancer and long-term survival: a meta-analysis. Ann Surg Oncol. 2012;19(9):2822-2832. doi:10.1245/s10434-011-2209-y

14.

Kasi

Abbasi

Handa

, et al. Total neoadjuvant therapy vs standard therapy in locally advanced rectal cancer: a systematic review and meta-analysis. JAMA Netw Open. 2020;3(12):e2030097. doi:10.1001/jamanetworkopen.2020.30097

15.

Martin

Heneghan

Winter

. Systematic review and meta-analysis of outcomes following pathological complete response to neoadjuvant chemoradiotherapy for rectal cancer. Br J Surg. 2012;99(7):918-928. doi:10.1002/bjs.8702

16.

Sell

Qwaider

Goldstone

, et al. Ten-year survival after pathologic complete response in rectal adenocarcinoma. J Surg Oncol. 2021;123(1):293-298. doi:10.1002/jso.26247

17.

Ferrari

Fichera

. Neoadjuvant chemoradiation therapy and pathological complete response in rectal cancer. Gastroenterol Rep (Oxf). 2015;3(4):277-288. doi:10.1093/gastro/gov039

18.

Bitterman

Resende Salgado

Moore

, et al. Predictors of complete response and disease recurrence following chemoradiation for rectal cancer. Front Oncol. 2015;5:286. doi:10.3389/fonc.2015.00286

19.

Zeng

Liang

Wang

, et al. Clinical parameters predicting pathologic complete response following neoadjuvant chemoradiotherapy for rectal cancer. Chin J Cancer. 2015;34(10):468-474. doi:10.1186/s40880-015-0033-7

20.

Huh

Kim

. Clinical prediction of pathological complete response after preoperative chemoradiotherapy for rectal cancer. Dis Colon Rectum. 2013;56(6):698-703. doi:10.1097/DCR.0b013e3182837e5b

21.

McCawley

Clancy

O’Neill

Deasy

McNamara

Burke

. Mucinous rectal adenocarcinoma is associated with a poor response to neoadjuvant chemoradiotherapy: a systematic review and meta-analysis. Dis Colon Rectum. 2016;59(12):1200-1208. doi:10.1097/DCR.0000000000000635

22.

Hur

Kim

Min

, et al.

Can a biomarker-based scoring system predict pathologic complete response after preoperative chemoradiotherapy for rectal cancer?

Dis Colon Rectum. 2014;57(5):592-601. doi:10.1097/DCR.0000000000000109

23.

Xiao

Guo

, et al. A genotype signature for predicting pathologic complete response in locally advanced rectal cancer. Int J Radiat Oncol Biol Phys. 2021;110(2):482-491. doi:10.1016/j.ijrobp.2021.01.005

24.

Restivo

Zorcolo

Cocco

, et al. Elevated CEA levels and low distance of the tumor from the anal verge are predictors of incomplete response to chemoradiation in patients with rectal cancer. Ann Surg Oncol. 2013;20(3):864-871. doi:10.1245/s10434-012-2669-8

25.

Wallin

Rothenberger

Lowry

Luepker

Mellgren

. CEA – a predictor for pathologic complete response after neoadjuvant therapy for rectal cancer. Dis Colon Rectum. 2013;56(7):859-868. doi:10.1097/DCR.0b013e31828e5a72

26.

Kleiman

Al-Khamis

Farsi

, et al. Normalization of CEA levels post-neoadjuvant therapy is a strong predictor of pathologic complete response in rectal cancer. J Gastrointest Surg. 2015;19(6):1106-1112. doi:10.1007/s11605-015-2814-3

27.

Huang

Lan

, et al. CEA Clearance pattern as a predictor of tumor response to neoadjuvant treatment in rectal cancer: a post-hoc analysis of FOWARC trial. BMC Cancer. 2018;18(1):1145. doi:10.1186/s12885-018-4997-y

28.

Yamamoto

Toiyama

Okugawa

, et al. Clinical implications of pretreatment: lymphocyte-to-monocyte ratio in patients with rectal cancer receiving preoperative chemoradiotherapy. Dis Colon Rectum. 2019;62(2):171-180. doi:10.1097/DCR.0000000000001245

29.

Cheong

Shin

Suh

. Prognostic value of changes in serum carcinoembryonic antigen levels for preoperative chemoradiotherapy response in locally advanced rectal cancer. World J Gastroenterol. 2020;26(44):7022-7035. doi:10.3748/wjg.v26.i44.7022

30.

Das

Skibber

Rodriguez-Bigas

, et al. Predictors of tumor response and downstaging in patients who receive preoperative chemoradiation for rectal cancer. Cancer. 2007;109(9):1750-1755. doi:10.1002/cncr.22625

31.

Zhang

Cai

Xie

, et al. Nomogram for predicting pathological complete response and tumor downstaging in patients with locally advanced rectal cancer on the basis of a randomized clinical trial. Gastroenterol Rep (Oxf). 2020;8(3):234-241. doi:10.1093/gastro/goz073

32.

de Campos-Lobato

Geisler

da Luz Moreira

Stocchi

Dietz

Kalady

. Neoadjuvant therapy for rectal cancer: the impact of longer interval between chemoradiation and surgery. J Gastrointest Surg. 2011;15(3):444-450. doi:10.1007/s11605-010-1197-8

33.

Glehen

Chapet

Adham

Nemoz

Gerard

, Lyons Oncology Group. Long-term results of the Lyons R90-01 randomized trial of preoperative radiotherapy with delayed surgery and its effect on sphincter-saving surgery in rectal cancer. Br J Surg. 2003;90(8):996-998. doi:10.1002/bjs.4162

34.

Kim

Cho

Kim

. Optimal time interval for surgery after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: analysis of health insurance review and assessment service data. Ann Coloproctol. 2018;34(5):241-247. doi:10.3393/ac.2018.01.01

35.

Lefevre

Mineur

Kotti

, et al. Effect of interval (7 or 11 weeks) between neoadjuvant radiochemotherapy and surgery on complete pathologic response in rectal cancer: a multicenter, randomized, controlled trial (GRECCAR-6). J Clin Oncol. 2016;34(31):3773-3780. doi:10.1200/JCO.2016.67.6049

36.

Gambacorta

Masciocchi

Chiloiro

, et al. Timing to achieve the highest rate of pCR after preoperative radiochemotherapy in rectal cancer: a pooled analysis of 3085 patients from 7 randomized trials. Radiother Oncol. 2021;154:154-160. doi:10.1016/j.radonc.2020.09.026

37.

de la Chapelle

Hampel

. Clinical relevance of microsatellite instability in colorectal cancer. J Clin Oncol. 2010;28(20):3380-3387. doi:10.1200/JCO.2009.27.0652

38.

Klarskov

Holck

Bernstein

, et al. Challenges in the identification of MSH6-associated colorectal cancer: rectal location, less typical histology, and a subset with retained mismatch repair function. Am J Surg Pathol. 2011;35(9):1391-1399. doi:10.1097/PAS.0b013e318225c3f0

39.

Nazemalhosseini Mojarad

Kashfi

Mirtalebi

, et al. Low level of microsatellite instability correlates with poor clinical prognosis in stage II colorectal cancer patients. J Oncol. 2016;2016:2196703. doi:10.1155/2016/2196703

40.

Acar

Kamer

, et al.

Do microsatellite instability (MSI) and deficient mismatch repair (dMMR) affect the pathologic complete response (pCR) in patients with rectal cancer who received neoadjuvant treatment?

Updates Surg. 2020;72(1):73-82. doi:10.1007/s13304-019-00697-2

41.

Uram

Wang

, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372(26):2509-2520. doi:10.1056/NEJMoa1500596

42.

Combination Chemotherapy, Bevacizumab, and/or Atezolizumab in Treating Patients With Deficient DNA Mismatch Repair Metastatic Colorectal Cancer, the COMMIT Study (NCT02997228): Accessed May 17, 2018.

A Predictive Model to Evaluate Pathologic Complete Response in Rectal Adenocarcinoma

Abstract

Keywords

Introduction

Methods and Materials

Patient Selection

Treatment Technique and Patients’ Follow-Up

Formulas and Statistical Analysis

Results

The Patients’ Clinical, Treatment, and Histopathological Characteristics

Response to nCRT

Predictive Model of pCR for RC Patients

Ultra-Low RC Patients

Discussion

Conclusion

Footnotes

Abbreviations

Acknowledgments

Authors’ Contributions

Declaration of Conflicting Interests

Ethical Approval

Funding

ORCID iD

References