Preoperative inflammatory markers combined with tumor stage to predict the prognosis of colorectal cancer

doi:10.21203/rs.3.rs-1539688/v1

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Preoperative inflammatory markers combined with tumor stage to predict the prognosis of colorectal cancer

https://doi.org/10.21203/rs.3.rs-1539688/v1

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Purpose: To explore the role of preoperative inflammatory markers (neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocytes level) combined with tumor stage in the prognostic evaluation of colorectal cancer (CRC).

Methods: A total of 70 CRC patients who were operated on between June 2016 and February 2019 were included in this study. A prognostic nomogram was established based on the integration of tumor stage prognostic factors with neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte level, and compared with a nomogram based only on the prognostic factors of tumor stage. Survival risk and prediction accuracy were assessed by using the Harrell's concordance index (c-index).

Results: The results of univariate analysis showed that high NLR, high PLR and low lymphocytes were significantly associated with reduced overall survival (OS) [HR:2.600, 95%CI: 1.008-6.711, P=0.0482; HR: 3.912, 95%CI: 1.427-10.73, P=0.008; HR:4.197, 95%CI: 1.623-10.86, P=0.003]. Furthermore, we contrasted the prediction accuracy of the three models, in which inflammation markers combined with tumor stage prediction accuracy [C-index: 0.803,95%CI: 0.711-0.895] was higher than inflammation markers alone or tumor stage [C-index: 0.735, 95%CI: 0.623-0.847; C-index: 0.787, 95%CI: 0.709-0.865], and constructed a nomogram.

Conclusion: Preoperative inflammatory markers combined with tumor stage can better predict the prognosis of patients with colorectal cancer compared with inflammatory markers or tumor stage alone.

Inflammation biomarkers

Colorectal cancer

Prognostic factors

Nomogram

Colorectal cancer (CRC) is one of the most common malignant tumors in China, ranking third and second in cancer incidence and mortality rates worldwide(Sung et al., 2021). In recent years, with advances in surgical techniques and other therapies, the overall survival (OS) of CRC patients has been significantly improved, but 40% -50% of patients still die due to tumor metastasis or recurrence after receiving surgical treatment(Rao et al., 2012). Currently, the TNM staging system is the most commonly used predictor of OS and recurrence for CRC(Zhan et al., 2017), However, the TNM staging system evaluates only the clinicopathological features of cancer patients, and limitations of the prognostic role of CRC based on TNM have been reported, especially in patients with positive lymph node metastasis (stage III)(Wang et al., 2020). Therefore, in clinical practice, we should combine multiple tumor biological markers or therapeutic parameters combined with TNM staging for a comprehensive analysis.

Several studies have shown that tumor development is closely related to inflammation, and it is reflected by the inflammatory response of the host(Wang et al., 2020). Systemic inflammatory response (SIR) markers, including C reactive protein (CRP)(Kubo et al., 2016), Glasgow Prognostic Score (GPS)(Zhang et al., 2016), Platelet-to-lymphocyte ratio(PLR), Lymphocyte-to-monocyte ratio (LMR)(Szkandera et al., 2014), associated with low survival in CRC and many other cancers(Kubo et al., 2016;Mahsuni et al., 2016). Recently, the inflammatory markers NLR and PLR have been shown to be potential prognostic predictors of CRC(Maeda et al., 2016;Mahsuni et al., 2016;Szkandera et al., 2014). However, there were no studies till date that have explored the role of preoperative inflammatory markers (NLR, PLR, and lymphocyte level) combined with tumor stage in CRC patients, compared with separate inflammatory markers or tumor stage.

Therefore, this study mainly evaluates the accuracy of prognosis prediction of preoperative inflammatory markers and tumor stage in CRC patients, explored the role of preoperative inflammatory markers and tumor stage in predicting the prognosis of CRC patients, and constructed a nomogram to provide a simple tool for prognosis prediction in CRC patients.

2.1. Patient Selection

Patients with pathologically confirmed colorectal adenocarcinoma who underwent surgical resection between June 2016 and February 2019 were enrolled in this study. Surgical procedures in all patients were performed by the same surgical team in the same department. Exclusion criteria included patients presenting with clinical symptoms of systemic inflammation or infection, hematologic disease, evidence of high fever, intestinal fibrosis, episodes of intestinal obstruction during hospitalization, or other malignancy.

2.2. Clinical data

Neutrophil count, lymphocyte count, red blood cells (RBC), and platelet count measured within 7 days before surgery were collected. The NLR or PLR was calculated by dividing the absolute number of neutrophils or platelets by the absolute number of lymphocytes, respectively.

Clinical data were collected through the hospital information system, including age, sex, tumor stage, and tumor size. Tumor staging was performed according to the tumor-node-metastasis (TNM) classification of the American Joint Committee on Cancer (AJCC, 8th edition).

2.3. Survival and follow-up

Follow-up information was collected from the hospital records, and some patients were followed up by telephone, SMS and E-mail, and the duration was calculated from the operation date to the date of the last follow-up (March 1,2022). OS was calculated from the date of diagnosis to the survivor death or last follow-up.

2.4. Statistical analysis

Version SPSS 23.0 (IBM Corp, Armonk, NY, USA) was used to perform the statistical analysis. The distribution of baseline characteristics was compared using either an unpaired t-test or a ANOVA-test. Cutoff values for the NLR and PLR were determined and analyzed for survival using the X-tile software.

The Kaplan-Meier method was used to generate OS curves, and the Log-rank test was used to compare differences in variables. Covariates showing dominance (P < 0.05) in the univariate analysis were entered into the Cox regression model for multivariate analysis. P < 0.05 was considered statistically significant.

The nomogram model was developed using R 4.1.2. Concordance index (C-index), subject operating characteristics (ROC) curves were further used to evaluate the prediction performance. Values of P < 0.05 were considered statistically significant.

3.1. Patient information

For inclusion and exclusion conditions, 70 patients were included, including 31 male and 39 female patients, with an age ranging from 45 to 95 years old (Table 1).

Table 1

Demographic Data
Characteristics	(n = 70)	%
Age(years)	68(45–95)	NA
Sex
Female	39	55.71%
Male	31	44.29%
tumor size(cm)	4.48(1.2–10.0)	NA
clinlic stage
stage Ⅰ	9	12.86%
stage Ⅱ	33	47.14%
stage Ⅲ	25	35.71%
stage Ⅳ	3	4.29%
NLR level	3.66(1.08–23.10)	NA
PLR level	199.97(77.05-531.94)	NA
neutrophils level
normal	62	88.57%
low	3	4.29%
high	5	7.14%
lymphocytes level
normal	62	88.57%
low	8	11.43%
Platelet
normal	47	67.14%
low	1	1.43%
high	22	31.43%

3.2. To determine the optimal cutoff value for the NLR and PLR

According to the X-tile plot, the optimal cut-off for the NLR is 5.50 (Figs. 1A and B) and the PLR is 305.88 (Figs. 1D and E). The OS rate was 75% in the very low NLR group (less than 5.50), compared with 40% in the high NLR group (greater than 5.50) (Fig. 1C). The OS rate in the low PLR group (less than 305.88) was 74.19%, while the OS rate in the high PLR group (greater than 305.88) was 37.50% (Fig. 1F).

3.3. Correlation between clinicopathological factors and OS

To assess the relationship of individual clinicopathological parameters and pre-treatment levels with prognosis for NLR, PLR, and lymphocyte levels, a univariate analysis was performed. Sex, NLR, PLR, lymphocyte level, and tumor stage were significantly associated with OS, while sex showed no correlation (all P-values < 0.05, Table 2). Higher NLR (> 5.50), high PLR (> 305.88), low lymphocyte levels, age (> 60 years), and male patients had worse outcomes (Fig. 2).

Table 2

Univariate Analyses of Prognostic Factors for Overall Survival
	Univariate Analysis	P value
Age(years)	5.78(0.775–43.14)	0.087
Sex	3.16(1.27–7.87)	0.013
tumor size
≤ 3.5cm	1(reference)	NS
༞3.5cm	0.62(0.25–1.54)	0.301
clinlic stage
stage Ⅰ	1(reference)	NS
stage Ⅱ	2.08(0.26–16.91)	0.494
stage Ⅲ	5.69(0.73–44.56)	0.098
stage Ⅳ	38.22(3.67-397.55)	0.002
NLR
≤ 5.50	1(reference)	NS
༞5.50	2.60(1.01–6.71)	0.048
PLR
≤ 305.88	1(reference)	NS
༞305.88	3.91(1.43–10.73)	0.008
neutrophils
normal	1(reference)	NS
low	0.00( 0.00-Inf)	0.997
high	1.27(0.29–5.40)	0.759
lymphocytes
normal	1(reference)	NS
low	4.20(1.62–10.86)	0.003
Platelet
normal	1(reference)	NS
low	0.00(0.00-Inf)	0.998
high	1.10(0.44–2.73)	0.833

Five covariates with statistical significance were entered into a multivariate Cox analysis. Age and sex were independent prognostic factors (P < 0.05, Table 3).

Table 3

Cox Multivariate Analyses of Prognostic Factors for Overall Survival
	Multivariate analysis	P value
Age(years)	9.27(1.07–79.96)	0.043
Sex	3.17(1.23–8.19)	0.017
clinlic stage
stage Ⅰ	1(reference)	NS
stage Ⅱ	1.29(0.14–11.51)	0.821
stage Ⅲ	4.25(0.51–35.22)	0.178
stage Ⅳ	10.35(0.84-127.09)	0.068
NLR
≤ 5.50	1(reference)	NS
༞5.50	0.58(0.07–4.57)	0.607
PLR
≤ 305.88	1(reference)	NS
༞305.88	1.62(0.09–29.75)	0.744
lymphocytes
normal	1(reference)	NS
low	4.47(0.35–57.62)	0.251

3.4. Nomogram of preoperative inflammatory markers and tumor staging for OS prediction

To assess the prognostic value of inflammatory markers plus tumor stage in CRC, a nomogram analysis was performed for OS (Fig. 3). The C-index of the nomogram of tumor stage, inflammatory markers and inflammatory markers plus tumor stage was 0.787, 0.735 and 0.803, respectively.

These results indicate that although the prognosis of inflammatory markers alone is poor with clinical stage, the combination of inflammatory markers with clinical stage can improve the role of clinical stage in predicting CRC prognosis.

3.5. Preoperative inflammatory markers combined with tumor stage can effectively predicting the OS in CRC

As mentioned above, although preoperative inflammatory markers combined with tumor stage is the most valuable in predicting OS relative to inflammatory markers and tumor stage, to further evaluate the efficacy of this model to the 1-year OS, 3-year OS and 5-year OS prediction, we evaluated it by drawing ROC curves (Fig. 4). From these ROC plots showed that the predictive effect of combining preoperative inflammatory markers and tumor stage was the best whether in predicting 1-year OS and 3-year OS, or 5-year OS.

In this study, we investigated the correlation between NLR, PLR, lymphocytes leves, tumor stage, and overall survival in patients with primary CRC who underwent surgical resection. The results showed that high NLR, high PLR and low lymphocytes were significantly associated with reduced OS. In addition, we study proved that the prognosis prediction of preoperative inflammatory markers combined with tumor stage was better than the inflammatory markers or tumor stage alone (C index: preoperative inflammatory markers combined with tumor stage was 0.803, tumor stage was 0.787 and inflammatory markers was 0.735). We also constructed a nomogram model based on preoperative inflammatory markers combined with tumor staging, which provides an effective and simple tool for the prognosis prediction of CRC.

Recently, significant associations between host systemic inflammatory response and tumor progression and tumor characteristics have been demonstrated in several studies(Mantovani et al., 2008;McMillan, 2013). Our results also further demonstrate the prognostic correlation of NLR, PLR and lymphocyte levels with CRC, consistent with relevant studies in recent years, although clinical values vary across studies(Zhang et al., 2017). In this study, we determined the optimal cutoff value for inflammatory biomarkers using the powerful X-tile program graphical tool, therefore, we believe that our results are reliable.

Based on the above findings, we constructed a nomogram based on preoperative inflammatory markers (NLR, PLR and lymphocytes levels) combined with tumor stage. The c-index value of this model is much higher than that in recent similar reports(Li et al., 2018) and higher than the c-index based on TNM staging characteristics (0.787). To further confirm the performance of the new nomogram model, additional statistical tools for the ROC curves were applied. The results also showed that the model predicted the AUC value of 5-year OS at 0.921, which is higher than the preoperative inflammatory markers or tumor stage alone.

But our study also has limitations. First, this study is a single-center, retrospective study. Second, the sample size is small and may lead to the selection offset of the data. Finally, because the model only includes tumor stage, inflammatory markers (NLR, PLR and lymphocyte levels) and basic patient information (age, sex), it ignores other potential factors such as the differentiation degree of the tumor, tumor site and other factors. Despite these limitations, our study still shows that inflammatory markers plus tumor staging can improve the prognostic predictive value of tumor stage for CRC patients .

We constructed a new prognostic evaluation model based on tumor stage, preoperative inflammatory markers (NLR, PLR, and lymphocyte levels), and basic patient information (age, sex). A nomogram of preoperative inflammatory markers (NLR, PLR and lymphocyte levels) into traditional prognostic factors (tumor stage, age, sex) improves the prediction accuracy of 5-year outcome in these patients. Since NLR and PLR are easily available parameters that can be obtained from conventional blood cell counts, this model may be of clinical value for prognostic outcomes in CRC patients.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Bingbing Li and Yihong Zheng. The first draft of the manuscript was written by Bingbing Li and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethics approval

This is an retrospective study. The Guangdong Provincial People' s Hospital Ganzhou Hospital (Ganzhou Municipal Hospital) Research Ethics Committee has confirmed that no ethical approval is required.

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No competing interests reported.

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Preoperative inflammatory markers combined with tumor stage to predict the prognosis of colorectal cancer

Status:

Version 1

Abstract

Figures

1. Background

2. Materials And Methods

2.1. Patient Selection

2.2. Clinical data

2.3. Survival and follow-up

2.4. Statistical analysis

3. Results

3.1. Patient information

3.2. To determine the optimal cutoff value for the NLR and PLR

3.3. Correlation between clinicopathological factors and OS

3.4. Nomogram of preoperative inflammatory markers and tumor staging for OS prediction

3.5. Preoperative inflammatory markers combined with tumor stage can effectively predicting the OS in CRC

4. Discussion

5. Conclusion

Declarations

References

Additional Declarations

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