Comparison of the efficacy and construction of prediction model for relapse free survival in breast cancer based on diabetes mellitus type 2

doi:10.3760/cma.j.cn371439-20240716-00050

Abstract

Abstract:

Objective To construct univariate and multivariate relapse free survival （RFS） prediction models for breast cancer patients with diabetes mellitus type 2 （T2DM） and to compare and select the model with higher predictive performance. Methods A total of 912 breast cancer patients treated at the First Affiliated Hospital of Dalian Medical University from January 2010 to December 2016 were included， of which 202 patients had T2DM and 710 patients did not. Kaplan-Meier survival curve was drawn based on whether patients had T2DM， and log-rank test was performed based on whether patients had T2DM. All patients were randomly divided into a training set （n=640） and a validation set （n=272） at a ratio of 7∶3. Univariate and multivariate Cox proportional risk regression models were used to analyze RFS in breast cancer patients with the survival package. The "rms" package was employed to construct univariate and multivariate RFS prediction models for breast cancer patients with T2DM. Clinical decision curves and calibration curves were used to validate the models. The receiver operator characteristic （ROC） curve was used to compare and analyze the prediction performance of the two models. Results There were no statistically significant differences between the training set and the validation set patients in terms of age， T2DM， surgical approach， axillary management methods， T stage， N stage， molecular sub-type， estrogen receptor （ER）1， ER2， progesterone receptor （PR）， ER and PR consistency， Ki67， human epidermal growth factor receptor 2 （HER2）（all P>0.05）. There was a statistically significant difference in histological grade （χ²=7.59， P=0.022）. Survival analysis showed that the 5-year RFS rate was 83.7% in patients with T2DM and 92.3% in patients without T2DM （χ²=16.61， P<0.001）. Univariate analysis revealed that age （HR=1.04， 95%CI： 1.03-1.06， P<0.001）， T2DM （HR=2.31， 95%CI： 1.49-3.55， P<0.001）， surgical approach （HR=2.39， 95%CI： 1.20-4.77， P=0.013）， axillary management methods （HR=2.62， 95%CI： 1.72-3.98， P<0.001）， T stage （T₂： HR=2.13， 95%CI： 1.36-3.31， P<0.001； T₃： HR=6.90， 95%CI： 3.35-14.22， P<0.001）， N stage （N₂： HR=3.87， 95%CI： 2.12-7.07， P<0.001； N₃： HR=8.61， 95%CI： 4.71-15.75， P<0.001）， molecular sub-type （Luminal B： HR=2.74， 95%CI： 1.17-6.36， P=0.019； HER2⁺： HR=3.64， 95%CI： 1.38-9.58， P=0.009； TNBC： HR=4.40， 95%CI： 1.71-11.34， P=0.002）， ER1 （>10%： HR=0.57， 95%CI： 0.37-0.90， P=0.016）， ER2 （HR=0.57， 95%CI： 0.37-0.89， P=0.015）， and PR （HR=0.56， 95%CI： 0.37-0.86， P=0.008） were all factors influencing RFS in breast cancer patients. Multivariate analysis demonstrated that age （HR=1.04， 95%CI： 1.02-1.06， P<0.001）， T2DM （HR=1.82， 95%CI： 1.16-2.85， P=0.009）， T stage （T₂： HR=1.60， 95%CI： 1.01-2.54， P=0.046； T₃： HR=2.64， 95%CI： 1.22-5.72， P=0.014）， N stage （N₂： HR=3.72， 95% CI： 2.01-6.88， P<0.001； N₃： HR=5.34， 95%CI： 2.78-10.25， P<0.001）， and ER1 （>10%： HR=0.63， 95%CI： 0.39-0.99， P=0.046） were independent factors influencing RFS in breast cancer patients. Based on the 10 and 5 variables with P<0.05 in the univariate and multivariate analyses respectively， the nomograms of the univariate and multivariate prediction models were constructed to evaluate the influence of factors such as T2DM on the postoperative RFS of breast cancer patients. Clinical decision curves and calibration curves indicated that both models had high predictive value for RFS in breast cancer patients， and the predictive results were highly consistent with the actual observed results. ROC curve analysis showed that there was no statistically significant difference in the area under the curve （AUC） of the two models for predicting the RFS rates of breast cancer patients in the training set and validation set at 36， 60， and 84 months （all P>0.05）， indicating that the predictive efficacy of the two models was comparable. The multivariate model is more suitable for clinical application because it uses fewer variables. Conclusions Breast cancer patients with T2DM have poorer prognosis. Age， T2DM， T stage， N stage， and ER1 are independent factors influencing postoperative RFS in breast cancer patients. The multi-factor prediction model of RFS in breast cancer patients based on T2DM is more suitable for clinical application due to its higher predictive efficacy and fewer variables.

Key words: Breast neoplasms, Diabetes mellitus， type 2, Relapse free survival, Nomograms, Dual models

Zhou Wenkao, Huang Hesen, Pan Yimei, Huang Lingyan, Wang Mingshan, Zhao Fangli, Wang Ya, Tang Huimin. Comparison of the efficacy and construction of prediction model for relapse free survival in breast cancer based on diabetes mellitus type 2[J]. Journal of International Oncology, 2025, 52(5): 295-303.

Figures/Tables 8

References 27

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项目	训练集（n=640）			验证集（n=272）		t/χ²值	P值
年龄（岁）	54.81±11.63			54.54±11.47		0.16	0.872
T2DM
否	495（77.3）			215（79.0）		0.32	0.572
是	145（22.7）			57（21.0）		0.32	0.572
手术方式
保乳手术	134（20.9）			58（21.3）		0.02	0.896
乳房切除术	506（79.1）			214（78.7）		0.02	0.896
腋窝处理方法
腋窝淋巴清扫	416（65.0）			188（69.1）		1.45	0.229
前哨淋巴结活检	224（35.0）			84（30.9）		1.45	0.229
组织学分级
高分化	47（7.3）			30（11.1）
中分化	272（42.5）			92（33.8）		7.59	0.022
低分化	321（50.2）			150（55.1）
T分期
T₁		429（67.0）	181（66.5）		0.03		0.984
T₂		194（30.3）	84（30.9）
T₃		17（2.7）	7（2.6）
N分期
N₀		459（71.7）	192（70.6）		3.29		0.349
N₁		119（18.6）	50（18.4）
N₂		44（6.9）	16（5.9）
N₃		18（2.8）	14（5.1）
分子分型
Luminal A		114（17.8）	49（18.0）		5.34		0.148
Luminal B		391（61.1）	161（59.2）
HER2⁺		75（11.7）	24（8.8）
TNBC		60（9.4）	38（14.0）
ER1^a
<1%		142（22.5）	70（26.1）
1%~10%		38（6.0）	20（7.4）		2.19		0.335
>10%		450（71.4）	179（66.5）
ER2
<1%		142（22.2）	70（25.7）		1.35		0.246
≥1%		498（77.8）	202（74.3）		1.35		0.246
PR
<1%		207（32.3）	92（33.8）		0.19		0.663
≥1%		433（67.7）	180（66.2）		0.19		0.663
ER和PR一致性
否		557（87.0）	234（86.0）		0.17		0.683
是		83（13.0）	38（14.0）		0.17		0.683
Ki67
<5%		44（6.9）	20（7.4）
5%~30%		396（61.9）	157（57.7）		1.40		0.496
>30%		200（31.2）	95（34.9）
HER2
阴性		155（24.2）	60（22.1）
弱阳性		304（47.5）	136（50.0）		0.63		0.729
阳性		181（28.3）	76（27.9）

变量		β值		SE值	Waldχ²值	HR值	95%CI	P值
年龄（岁）		0.04		0.01	4.57	1.04	1.03~1.06	<0.001
T2DM
否						Ref
是		0.83		0.22	3.79	2.31	1.49~3.55	<0.001
手术方式
保乳手术						Ref
乳房切除术		0.87		0.35	2.48	2.39	1.20~4.77	0.013
腋窝处理方法
腋窝淋巴清扫						Ref
前哨淋巴结活检		0.96		0.21	4.48	2.62	1.72~3.98	<0.001
组织学分级
高分化						Ref
中分化		-0.24		0.46	0.52	0.78	0.32~1.93	0.598
低分化		0.51		0.42	1.20	1.67	0.72~3.87	0.229
T分期
T₁						Ref
T₂		0.75		0.22	3.35	2.13	1.36~3.31	<0.001
T₃		1.93		0.36	5.24	6.90	3.35~14.22	<0.001
N分期
N₀						Ref
N₁		0.46		0.28	1.62	1.59	0.91~2.79	0.104
N₂		1.35		0.31	4.39	3.87	2.12~7.07	<0.001
N₃		2.15		0.31	6.98	8.61	4.71~15.75	<0.001
分子分型
Luminal A						Ref
Luminal B		1.01		0.43	2.34	2.74	1.17~6.36	0.019
HER2⁺		1.29		0.49	2.61	3.64	1.38~9.58	0.009
TNBC		1.48		0.48	3.06	4.40	1.71~11.34	0.002
ER1
<1%						Ref
1%~10%	-0.29		0.44		0.66	0.74	0.31~1.78	0.504
>10%	-0.55		0.22		2.39	0.57	0.37~0.90	0.016
ER2
<1%						Ref
≥1%	-0.55		0.22		2.43	0.57	0.37~0.89	0.015
PR
<1%						Ref
≥1%	-0.56		0.21		2.64	0.56	0.37~0.86	0.008
ER和PR一致性
否						Ref
是	0.24		0.29		0.83	1.27	0.72~2.26	0.405
Ki67
<5%						Ref
5%~30%	0.45		0.52		0.86	1.56	0.57~4.33	0.387
>30%	0.61		0.53		1.14	1.83	0.65~5.19	0.252
HER2
阴性						Ref
弱阳性	0.01		0.27		0.03	1.01	0.59~1.72	0.973
阳性	0.16		0.29		0.54	1.17	0.66~2.09	0.585

变量	β值	SE值	Waldχ²值	HR值	95%CI	P值	变量	β值	SE值	Waldχ²值	HR值	95%CI	P值
年龄（岁）	0.04	0.01	3.81	1.04	1.02~1.06	<0.001	分子分型
T2DM							Luminal A				Ref
否				Ref			Luminal B	0.67	0.44	1.52	1.96	0.82~4.68	0.130
是	0.59	0.23	2.62	1.82	1.16~2.85	0.009	HER2⁺	0.41	0.82	0.50	1.50	0.30~7.49	0.619
手术方式							TNBC	0.46	0.82	0.56	1.59	0.32~7.98	0.573
保乳手术				Ref			ER1
乳房切除术	0.49	0.36	1.35	1.63	0.80~3.31	0.177	<1%				Ref
腋窝处理方法							1%~10%	-0.02	0.46	0.06	0.97	0.39~2.37	0.950
腋窝淋巴清扫				Ref			>10%	-0.47	0.24	1.99	0.63	0.39~0.99	0.046
前哨淋巴结活检	0.12	0.38	0.30	1.12	0.53~2.37	0.762	ER2
T分期							<1%				Ref
T₁				Ref			≥1%	NA	0.00		NA	NA，NA	-
T₂	0.47	0.24	1.99	1.60	1.01~2.54	0.046	PR
T₃	0.97	0.39	2.47	2.64	1.22~5.72	0.014	<1%				Ref
N分期							≥1%	-0.13	0.35	0.38	0.88	0.44~1.73	0.704
N₀				Ref
N₁	0.35	0.29	1.21	1.42	0.80~2.53	0.227
N₂	1.31	0.32	4.17	3.72	2.01~6.88	<0.001
N₃	1.67	0.33	5.02	5.34	2.78~10.25	<0.001