The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis

doi:10.21203/rs.3.rs-5023932/v1

Objective

Diabetes mellitus (DM) has been confirmed as a common risk factor for postoperative complications. This study aims to elucidate the impact of DM on postoperative complications following radical prostatectomy.

Methods

Using data from a national inpatient sample from 2016 to 2020, patients aged ≥ 18 years who were diagnosed with prostate cancer (PCa) and underwent radical prostatectomy were identified and divided into a DM group and a non-DM group. We further divided the DM group into uncomplicated DM and advanced DM groups. We compared the outcome variables between the three groups through univariate analysis and adjusted multivariate logistic regression.

Results

Seventeen thousand five hundred eighty-eight records were undergoing radical prostatectomy included in the present study, among which 2683 records (9.43%) had a diagnosis of DM. The DM group will incur higher costs (53,775 [38,286 − 65,482] vs. 51,546 [37,195 − 61,815] p < 0.001). After adjusting the variables with baseline differences in the multivariate regression models, DM was identified as an independent risk factor for unfavorable discharge (aOR = 1.20, 95%CI [1.02–1.42], P = 0.31), genitourinary complication (aOR = 1.40, 95%CI [1.13–1.73], P = 0.002), cardiac complication (aOR = 1.29, 95%CI [1.04–1.6], P = 0.019), and ventilatory support (aOR = 1.55, 95%CI [1.05–2.29], P = 0.028). After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group.

Conclusion

The findings suggest that DM is more likely to face adverse clinical outcomes and higher incidences of postoperative complications. It found that DM is an independent risk factor for adverse clinical outcomes after radical prostatectomy for cancer.

prostatectomy

prostate cancer

diabetes mellitus

postoperative complications

Prostate cancer (PCa) is the most prevalent malignancy among men in the United States (US) and the second leading cause of cancer-related mortality[1]. Prostate cancer and diabetes mellitus (DM) are the two most common public health concerns within the aging male demographic[2]. Radical prostatectomy (RP), conducted via open retropubic resection (ORP) or robot-assisted radical prostatectomy (RARP), is the reference standard for the treatment of prostate cancer. Several studies have investigated various risk factors associated with adverse outcomes following RP[3–6]. These studies reveal a significant correlation between adverse outcomes and factors such as patient age, family history, race, weight, dietary habits, smoking, hospital capacity, hospital bed size, and hospital teaching status.

The impact of DM on postoperative outcomes in patients undergoing RP remains debated. A meta-analysis included 17 cohort studies with 274,677 male patients concluded that pre-existing DM is associated with increased prostate cancer-specific mortality and all-cause mortality[7]. However, a Swedish cohort study reached the opposite conclusion, reporting no correlation between DM and prostate cancer after adjusting for confounding risk factors[8]. Jayachandran et al. studied diabetic patients undergoing RP and found a significant link between DM and higher postoperative complication rates, with obesity and race as crucial contributing factors.[9]. Considering these inconsistent research findings, this study aims to assess the impact of DM on postoperative complications following RP using a largest publicly accessible hospital discharge database.

Data Source

All patient data were extracted from the National Inpatient Sample (NIS) database between 2016 to 2020. The NIS, the largest publicly accessible hospital discharge database encompassing all payers in the US, is a component of the Healthcare Cost and Utilization Project supported by the Agency for Healthcare Research and Quality (AHRQ)[10]. It comprises approximately 20% of discharge summaries from community hospitals across the US, encompassing public hospitals and academic medical centers, thus enabling the derivation of national estimates. The NIS database contains various data elements, including primary and secondary diagnoses, primary and secondary procedures, admission type, patient demographics, expected payment source, length of hospital stay, and hospital characteristics. Since 2016, the NIS has utilized the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) codes.

Study Design

ICD-10-CM program codes (0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ) were used to identify patients underwent prostatectomy. We excluded subjects without a diagnosis of prostate malignancy (C61) and patients aged ≤ 18 years. Records missing critical data were excluded, while missing values for the race/ethnicity variable, exceeding 5%, were combined into the "Other" category. According to the presence or absence of diabetes diagnosis codes, patients included were divided into the DM group and the non-DM group. Additionally, patients in the DM group were further categorized as uncomplicated and advanced DM based on the presence of chronic DM-related complications. Details of the ICD-10-CM/PCS codes used are summarised in Table 1.

Table 1

ICD-10 codes for defining .
Variable	ICD-10 Codes
Diabetes Mellitus
Advanced diabetes mellitus	E08.2, E08.3, E08.4, E08.5, E08.6, E08.8, E09.2, E09.3, E09.4, E09.5, E09.6, E09.8, E10.2, E10.3, E10.4, E10.5, E10.6, E10.8, E11.2, E11.3, E11.4, E11.5, E11.6, E11.8, E13.2, E13.3, E13.4, E13.5, E13.6, E13.8
Uncomplicated diabetes mellitus	E08.0, E08.1, E08.9, E09.0, E09.1, E09.9, E10.1, E10.9, E11.0, E11.1, E11.9, E13.0, E13.1, E13.9, O24.0, O24.1, O24.3, O24.4, O24.8, O24.9
Prostate Malignancy	C61
Radical Prostatectomy	0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ

The baseline data included patient demographics and hospital characteristics. Patient demographics encompassed age, race, admission type, insurance status, primary expected payer, income quartile by zip code, admission type, and comorbidities. The burden of comorbidities was measured using the Elixhauser comorbidity index (ECI) and categorized as 0, 1, and ≥ 2[11, 12]. Since DM is the primary variable of interest in this study, we excluded the two DM-related categories when calculating the ECI. Hospital characteristics included hospital size, location, and teaching status. Age was continuously assessed.

The primary clinical outcomes of this study were length of stay (LOS), unfavorable discharge status, total hospital charges, and postoperative complications. Postoperative complications included ventilatory support, blood transfusion, postoperative pain, infection, deep vein thrombosis (DVT)/pulmonary embolism (PE), genitourinary, respiratory, cardiac, and gastrointestinal issues. Details of the ICD-10 codes used can be found in Supplementary Table 1. Transfer to a short-term hospital, home health care, or other transfers, including a skilled nursing facility, intermediate care, and another type of facility, was defined as unfavorable discharge[13, 14]. LOS and total hospital charges were calculated as continuous variables.

Statistical analysis

Continuous variables are presenting as medians and interquartile ranges owing to skewed data. Categorical variables are presented as proportions. The Mann-Whitney U test was utilized for comparing continuous variables, while categorical variables were analyzed with Pearson's chi-square test (with or without Yates' continuity correction). Fisher's exact test was applied when the chi-square test was inappropriate.

To examine the impact of DM on clinical outcomes, both univariate and multivariate comparisons were performed between the two groups. Univariate comparisons were conducted as previously described. For subset analysis, categorical variables were compared using the same methods. Kruskal–Wallis test was applied to compare continuous variables among the non-DM, uncomplicated DM, and advanced DM groups. Subsequently, unadjusted and adjusted multivariable logistic regression models were established. All baseline variables with significant differences were incorporated into the adjusted models, including age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region, and ECI. Finally, the same multivariable logistic regression models were performed to compare the clinical outcomes among the non-DM, uncomplicated DM, and advanced DM groups.

Patient selection and all statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC) and R software (version 4.3.3, R Foundation for Statistical Computing, Vienna, Austria). A p-value of < 0.05 was considered statistically significant.

Table 2 presents the baseline demographic and clinical feature data of the 17,588 patients included in the analysis, of which 2,683 (15.25%) were divided into the DM group. Patients with DM are older (65 [60–69] vs. 63 [58–67]) and have a higher proportion of black individuals (20.8% vs. 11.7%). They also have lower income level, with higher proportions in the first (23.1% vs. 17.2%) or second (25.3% vs. 22.9%) income level quartiles. Additionally, a lower proportion of these patients pay with private insurance (49.3% vs. 58.9%), and they generally have higher ECI scores (ECI ≥ 3: 10.5% vs. 5.2%).

Table 2

Characteristics of Hospitals and patients in DM or non-DM group undergoing radical prostectomy for prostate cancer, National Inpatient Sample 2016–2020.
Demographic Characteristics	Non-DM group n = 14905 (%)	DM group n = 2683 (%)	P-value	Uncomplicated DM group n = 2129 (%)	Advanced DM group n = 554 (%)	P-value
Demographic Characteristics	Non-DM group n = 14905 (%)	DM group n = 2683 (%)	P-value	Uncomplicated DM group n = 2129 (%)	Advanced DM group n = 554 (%)	Between two groups^c	Between three groups^d
Age (y, median, IQR)	63 [58–67]	65 [60–69]	< 0.001	64 [60–69]	66 [61–69]	0.009	< 0.001
Race/Ethnicity			< 0.001			< 0.001	< 0.001
White	70.8	56.6		57.7	52.5
Black	11.7	20.8		18.9	28.2
Hispanic	5.6	8.7		9.1	7.4
Other^a	11.9	13.8		14.3	11.9
Income Quartile by Zip Code			< 0.001			0.254	< 0.001
1st	17.2	23.1		23.3	22.0
2nd	22.9	25.3		25.0	26.5
3rd	26.5	26.6		26.0	29.1
4th	33.4	24.9		25.6	22.4
Primary Expected Payer			< 0.001			< 0.001	< 0.001
Medicare	33.8	41.3		39.5	48.4
Medicaid	3.6	5.0		4.7	5.8
Private	58.9	49.3		51.6	40.4
Other^b	3.8	4.4		4.2	5.4
Admission Type			0.566			0.414	0.618
Elective	96.5	96.8		3.1	3.8
Non-elective	3.5	3.2		96.9	96.2
Hospital Bed Size			0.411			0.948	0.757
Small	15.7	15.3		15.4	15.2
Medium	25.3	24.3		24.4	23.8
Large	59.1	60.4		60.3	61.0
Hospital Location/Teaching Status			0.185			0.687	0.383
Rural	2.6	2.8		3.0	2.3
Urban Non-teaching	11.1	12.2		12.3	11.7
Urban Teaching	86.3	85.0		84.8	85.9
Hospital Region			< 0.001			< 0.001	< 0.001
Northeast	26.0	24.5		25.5	20.8
Midwest	25.5	23.3		21.7	29.1
South	29.9	35.1		36.2	30.9
West	18.6	17.1		16.5	19.3
Elixhauser Comorbidity Index			< 0.001			< 0.001	< 0.001
0	36.1	11.9		13.5	6.0
1	41.5	47.3		49.0	40.4
2	17.2	30.3		28.9	35.6
≥3	5.2	10.5		8.6	18.1
^{a Includes Asian or Pacific Islander, Native American, other and missing}. ^{b Includes self−pay, no charge and others}. ^{Mann−Whitney U test was performed to compare age between three groups. Pearson’s chi−square tests with or without Yates’ continuity correction and Fisher’s exact tests were performed for categorical variables}. ^{c Between uncomplicated DM group and advanced DM group}. ^{d Among non−DM group, uncomplicated DM group and advanced DM group}.

After further categorization within the DM group, 2,129 patients (79.35%) were classified as having uncomplicated DM and 554 patients (20.65%) as having advanced DM. Similar baseline differences were observed between the uncomplicated DM and advanced DM groups, as well as among the three groups (Table 2).

Clinical outcomes are shown in Table 3. Longer LOS (1 [1–2] days vs. 1 [1–2] days, P < 0.001) and higher adjusted hospital charges ($53,775 [38,286 − 65,482] vs. $51,546 [37,195 − 61,815], P < 0.001) were observed in the DM group. Higher rates of unfavorable discharge (8.2% vs. 5.6% P < 0.001) and postoperative complications were also noted, including ventilatory support (1.4% vs. 0.7% p < 0.001), blood transfusion (1.1% vs. 0.6% P < 0.009), genitourinary (4.7% vs. 2.4% P < 0.001), respiratory (1.2% vs. 0.8% P = 0.015), cardiac (4.5% vs. 2.8% P < 0.001), and gastrointestinal (3.4% vs. 2.3% P < 0.001) complications. The unadjusted logistic regression results were consistent with these findings (Table 4). Further analysis within the DM group revealed significant differences between the uncomplicated DM and advanced DM subgroups. Advanced DM patients had higher hospital charges ($63,945 [44,808 − 77,453] vs. $52,129 [37,389 − 62,367], P < 0.001) and higher incidence of unfavorable discharge (11.4% vs. 7.4%, P = 0.002). They also experienced higher incidences of complications such as genitourinary (11.0% vs. 3.0%, P < 0.001), respiratory (2.3% vs. 0.9%, P = 0.007), cardiac (7.4% vs. 3.8%, P < 0.001), and gastrointestinal complications (5.8% vs. 2.8%, P < 0.001).

Table 3

Clinical outcomes of patients in DM or non-DM group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016–2020.
Clinical Outcomes	Non-DM group n = 14905 (%)	DM group n = 2683 (%)	P-value	Uncomplicated DM group n = 2129 (%)	Advanced DM group n = 554 (%)	P-value
Clinical Outcomes	Non-DM group n = 14905 (%)	DM group n = 2683 (%)	P-value	Uncomplicated DM group n = 2129 (%)	Advanced DM group n = 554 (%)	Between two groups^a	Between three groups^b
Length of Stay (d, median, IQR)	1 [1–2]	1 [1–2]	< 0.001	1 [1–2]	1 [1–2]	< 0.001	< 0.001
Adjusted Hospital Charges ($, median, IQR)	51,546 [37,195 − 61,815]	53,775 [38,286 − 65,482]	< 0.001	52,129 [37,389 − 62,367]	63,945 [44,808 − 77,453]	< 0.001	< 0.001
Unfavorable Discharge	5.6	8.2	< 0.001	7.4	11.4	0.002	< 0.001
Ventilatory Support	0.7	1.4	< 0.001	1.2	2.0	0.169	0.001
Blood Transfusion	0.6	1.1	0.009	0.9	1.8	0.064	0.005
Postoperative Pain	1.3	1.7	0.115	1.7	1.4	0.631	0.250
Infection	0.2	0.1	1.000	0.1	0.4	0.191	0.277
DVT/PE	0.1	0.1	0.532	0.1	0.2	1.000	0.538
Genitourinary	2.4	4.7	< 0.001	3.0	11.0	< 0.001	< 0.001
Respiratory	0.8	1.2	0.015	0.9	2.3	0.007	0.002
Cardiac	2.8	4.5	< 0.001	3.8	7.4	< 0.001	< 0.001
Gastrointestinal	2.3	3.4	< 0.001	2.8	5.8	< 0.001	< 0.001
^{Mann−Whitney U tests and Kruskal–Wallis test were performed for length of stay and adjusted hospital charges. Pearson’s chi−square tests with or without Yates’ continuity correction and Fisher’s exact tests were performed for postoperative complications}. ^{a Between uncomplicated DM group and advanced DM group}. ^{b Among non−DM group, uncomplicated DM group and advanced DM group}.

Table 4

Logistic Regression Analysis of Morbidity in Patients in DM group vs non-DM group undergoing radical prostatectomy for prostate cancer, National Inpatient Sample 2016–2020.
	Unadjusted			Adjusted^a
	Odds Ratio	95%CI	P-value	Odds Ratio	95%CI	P-value
Unfavorable Discharge	1.50	1.29–1.75	< 0.001	1.20	1.02–1.42	0.031
Ventilatory Support	1.93	1.33–2.82	0.001	1.55	1.05–2.29	0.028
Blood Transfusion	1.74	1.14–2.65	0.010	1.48	0.95–2.28	0.081
Postoperative Pain	1.30	0.94–1.80	0.116	1.17	0.83–1.64	0.364
Infection	0.97	0.33–2.80	0.949	0.67	0.22–1.98	0.464
DVT/PE	1.39	0.46–4.16	0.557	1.19	0.38–3.67	0.766
Genitourinary	2.02	1.64–2.49	< 0.001	1.40	1.13–1.73	0.002
Respiratory	1.62	1.09–2.39	0.016	1.22	0.82–1.83	0.329
Cardiac	1.66	1.35–2.04	< 0.001	1.29	1.04–1.60	0.019
Gastrointestinal	1.49	1.18–1.88	0.001	1.14	0.90–1.46	0.282
^{a Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index}.

After adjusting with baseline variables in the multivariable regression models, DM was identified as an independent risk factor for clinical outcomes, including unfavorable discharge (aOR = 1.20, 95%CI [1.02–1.42], P = 0.031), ventilatory support (aOR = 1.55, 95%CI [1.05–2.29], P = 0.028), genitourinary (aOR = 1.40, 95%CI [1.13–1.73], P = 0.002) and cardiac complications (aOR = 1.29, 95%CI [1.04–1.6], P = 0.019). (Table 4)

In the subgroup analysis, the non-DM group served as a reference for comparison. As shown in Table 5, though not statistically significant, higher incidences and odds were also observed in the uncomplicated DM group compared to the non-DM group. Patients in the advanced DM group undergoing RP exhibited significantly higher odds of several adverse outcomes compared to the non-DM group. These outcomes included unfavorable discharge (aOR 1.65, 95% CI [1.24–2.21], P = 0.001), blood transfusion (aOR 2.33, 95% CI [1.18–4.62], P = 0.015), genitourinary (aOR 2.96, 95% CI [2.19-4.00], P < 0.001), cardiac (aOR 1.94, 95% CI [1.37–2.74], P < 0.001), and gastrointestinal complications (aOR 1.67, 95% CI [1.13–2.45], P = 0.009).

Table 5

Logistic Regression Analysis of Morbidity in Patients in non-DM group, uncomlicated DM group or DM with chronic complications group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016–2020.
	DM Subgroups^a	Unadjusted			Adjusted^b
	DM Subgroups^a	Odds Ratio	95%CI	P-value	Odds Ratio	95%CI	P-value
Unfavorable Discharge	Uncomplicated DM group	1.34	1.12–1.60	0.001	1.09	0.90–1.31	0.389
Unfavorable Discharge	Advanced DM group	2.16	1.65–2.83	< 0.001	1.65	1.24–2.21	0.001
Ventilatory Support	Uncomplicated DM group	1.71	1.11–2.63	0.015	1.46	0.94–2.27	0.095
Ventilatory Support	Advanced DM group	2.80	1.50–5.24	0.001	1.83	0.93–3.50	0.067
Blood Transfusion	Uncomplicated DM group	1.43	0.87–2.35	0.154	1.25	0.75–2.07	0.396
Blood Transfusion	Advanced DM group	2.93	1.52–5.65	0.001	2.33	1.18–4.62	0.015
Postoperative Pain	Uncomplicated DM group	1.35	0.95–1.92	0.099	1.23	0.85–1.77	0.272
Postoperative Pain	Advanced DM group	1.12	0.55–2.28	0.761	0.96	0.46–1.98	0.907
Infection	Uncomplicated DM group	0.61	0.14–2.58	0.500	0.45	0.10–1.93	0.282
Infection	Advanced DM group	2.34	0.55–9.97	0.249	1.33	0.30–5.92	0.705
DVT/PE	Uncomplicated DM group	1.23	0.76–1.98	0.395	1.15	0.33–4.07	0.825
DVT/PE	Advanced DM group	3.12	1.75–5.57	< 0.001	1.30	0.17–10.24	0.800
Genitourinary	Uncomplicated DM group	1.28	0.98–1.68	0.072	0.95	0.72–1.25	0.689
Genitourinary	Advanced DM group	5.12	3.84–6.81	< 0.001	2.96	2.19-4.00	< 0.001
Respiratory	Uncomplicated DM group	1.31	0.38–4.51	0.665	0.99	0.61–1.60	0.955
Respiratory	Advanced DM group	1.68	0.22–12.71	0.614	2.00	1.09–3.65	0.024
Cardiac	Uncomplicated DM group	1.31	0.38–4.51	0.665	1.11	0.87–1.43	0.409
Cardiac	Advanced DM group	1.68	0.22–12.71	0.614	1.94	1.37–2.74	< 0.001
Gastrointestinal	Uncomplicated DM group	1.21	0.92–1.60	0.173	0.98	0.74–1.31	0.915
Gastrointestinal	Advanced DM group	2.56	1.77–3.72	< 0.001	1.67	1.13–2.45	0.009
^{a Non−DM group was used as a reference to compare with}. ^{b Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index}.

DM has long been a global health challenge. This study elucidates the impact of DM, particularly cases with DM-related complications, on postoperative outcomes after RP, including LOS, total hospital charges, discharge status, and postoperative complications. From 2015 to 2020, 18,057 patients in the NIS database were diagnosed with prostate cancer and received RP. After dividing these patients into DM and non-DM groups, we examined their demographic and hospital characteristics, total hospital charges, LOS, discharge status, and postoperative complication rates. Although DM is considered an independent predictor of poor prognosis in some studies on urinary surgery[15–17], few studies examine its impact on postoperative clinical outcomes, specifically in RP.

DM plays an essential role in the complications of most surgical operations: Tan et al. and Zhang et al. indicate that DM is a risk factor for postoperative complications such as infection, hematoma, and reoperation in various non-cardiac surgeries. Several studies have assessed the impact of DM on patients undergoing RP. Teber et al. found that type 2 diabetes mellitus patients need a longer time to recover urinary control ability than non-diabetes patients after LRP, which is more evident in patients with DM for more than five years[10]. Multiple studies have shown that DM is unrelated to the clinicopathological features and biochemical recurrence in patients with PCa treated with RP[9, 18, 19]. Among these, Jayakrishnan et al. analyzed data from 1,262 patients with PCa and suggested that diabetes significantly increased the risk of biochemical recurrence in obese white males. Lee et al. analyzed 2,716 subjects and found that poor preoperative glycemic control worsened tumor prognosis and urinary incontinence recovery. However, most of these studies were limited by small sample size, while others focused on the relationship between preoperative glycemic control and postoperative recurrence risk or survival outcomes[7, 20]. To our knowledge, few studies have independently reported the impact of DM on clinical outcomes after RP. This study is by far the first large-scale research to explore the relationship between DM and clinical outcomes after RP using the NIS database, incorporating over 17,000 patients with PCa.

Our results found that PCa patients with DM tend to be younger and have lower income levels. Hill-Briggs et al. also reported that patients with DM generally have lower incomes[21]. At the same time, the study by Jayakrishnan et al. did not find significant age differences between PCa patients with and without DM[9]. It is confirmed that white and non-Hispanic black individuals constitute a large portion of the diabetic population, a finding consistent with the conclusions of this study[22]. Compared to non-diabetic patients, those with DM incur higher costs for RP, likely due to the combined need for postoperative care and diabetes management[23].

In this study, the incidences of postoperative complications in the DM group were significantly higher, including unfavorable discharge, ventilatory support, genitourinary, respiratory, cardiac, and gastrointestinal complications. After adjusting for potential confounding factors, DM as an independent risk factor increased the risks of unfavorable discharge after RP by 20%, ventilatory support by 55%, genitourinary by 40% and cardiac by 29%. Zhang et al. also reached similar conclusions in their meta-analysis of postoperative complications after non-cardiac surgery[24]. After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group. Wong et al. found that blood glucose control affects the clinical outcomes of abdominal surgeries ( including RP ): preoperative glycated hemoglobin (HbA1c) levels between 6% and 7% are associated with a higher risk of certain complications. These complications include anastomotic leak, wound infection, significant complications, and an increase in overall postoperative complications. This further supports the hypothesis that DM is a potential risk factor for early complications after RP.

This study benefits from using a well-designed and comprehensive NIS database system. It includes substantial data, ensuring sufficient statistical power and producing convincing results. We recognize that our research has some limitations. This study possesses all the disadvantages of retrospective studies—selection bias, temporal variations in disease and treatment modalities, and unknown confounding factors. The design of the NIS database lacks definitions for diabetes control, so we cannot assess the effect of diabetes control on the outcome of postoperative complications. In addition, the NIS database lacks information on cancer's severity or pathological findings, which will help measure surgical indications, structural factors, case combinations, and disease attributes. Manual diagnostic coding may lead to inaccuracies and omissions in diagnostic information. The non-longitudinal data structure design prevents us from obtaining patients' baseline conditions upon admission. We also lack information on changes in health status during hospitalization and follow-up data.

For patients undergoing RP for PCa, those with DM are more likely to face adverse clinical outcomes and have higher incidences of postoperative complications. These differences are more pronounced in the population with DM-related complications. Our results highlight the association between diabetes and adverse clinical outcomes following RP, providing valuable insights into the perioperative management of prostate cancer patients and guidance for improved management strategies and better overall outcomes for this high-risk group.

Author Contribution

Yichao Han and Yue Chen wrote the main manuscript text and Hongyu Guan prepared table 1-5. Xujun Xuan and Cheng Luo prepared supplemental table 1. Daohu Wang is responsible for reviewing and revising manuscript. All authors reviewed the manuscript.

Conflict of Interest: The authors declare no conflicts of interest in this study.

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No competing interests reported.

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The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis

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Abstract

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Introduction

Materials and Methods

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Study Design

Statistical analysis

Results

Discussion

Conclusion

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Supplementary Files

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