Sociodemographic profile of the sample and influence on the incidence of CDK-EPI episodes
Sociodemographic characteristics revealed that of the 75 patients included in the study, the majority (n = 47) were in the age group above 50 years old, representing 62.7%, 39 were female (52.0%), 44 brown (95.7%), 29 had a partner (53.7%), and 46 lived in Fortaleza or the metropolitan area (61.3%). Regarding the level of education, it is emphasized that 10 (31.3%) patients had incomplete higher education, seven incomplete high school (21.9%), and six complete elementary school (18.8%) (Table 1).
Table 1
Sociodemographic profile and its influence on the reduction of CKD-EPI in patients undergoing chemotherapy under analysis of renal function at the Hospital Universitário Walter Cantídio from 2012 to 2018.
|
|
CDK-EPI (n = 450)b
|
|
|
Sample
|
Normal
|
Reduced
|
p-value
|
Age
|
|
|
|
|
|
|
|
Up to 50
|
28
|
37.3%
|
153*
|
71.5%
|
30
|
12.7%
|
<0.001
|
> 50
|
47
|
62.7%
|
61
|
28.5%
|
206*
|
87.3%
|
|
Sex
|
|
|
|
|
|
|
|
Female
|
39
|
52.0%
|
105
|
49.1%
|
147*
|
62.3%
|
0.005
|
Male
|
36
|
48.0%
|
109*
|
50.9%
|
89
|
37.7%
|
|
Race
|
|
|
|
|
|
|
|
White
|
1
|
2.2%
|
0
|
0.0%
|
15*
|
7.9%
|
< 0.001
|
Brown
|
44
|
95.7%
|
155*
|
100.0%
|
172
|
90.5%
|
|
Black
|
1
|
2.2%
|
0
|
0.0%
|
3
|
1.6%
|
|
Marital status
|
|
|
|
|
|
|
|
With partner
|
29
|
53.7%
|
77
|
49.4%
|
79
|
46.7%
|
0.638
|
Without partner
|
25
|
46.3%
|
79
|
50.6%
|
90
|
53.3%
|
|
Education
|
|
|
|
|
|
|
|
Illiterate
|
1
|
3.1%
|
0
|
0.0%
|
10*
|
9.5%
|
< 0.001
|
Incomplete elementary school
|
2
|
6.3%
|
1
|
0.9%
|
3*
|
2.9%
|
|
Complete elementary school
|
6
|
18.8%
|
21
|
19.3%
|
35*
|
33.3%
|
|
Incomplete high school
|
7
|
21.9%
|
10
|
9.2%
|
17*
|
16.2%
|
|
Complete high school
|
1
|
3.1%
|
11*
|
10.1%
|
1
|
1.0%
|
|
Incomplete higher
|
10
|
31.3%
|
44*
|
40.4%
|
26
|
24.8%
|
|
Graduated
|
5
|
15.6%
|
22*
|
20.2%
|
13
|
12.4%
|
|
Place of Birth
|
|
|
|
|
|
|
|
Fortaleza/Metropolitan area
|
46
|
61.3%
|
113
|
52.8%
|
153*
|
64.8%
|
0.010
|
Countryside
|
29
|
38.7%
|
101*
|
47.2%
|
83
|
35.2%
|
|
Data expressed as absolute frequency and percentage. * p < 0.05, Fisher's exact test or Pearson's chi-square. aSample unit = patient; bSample unit = episodes of CDK-EPI assessment. |
Patients over the age of 50 had a more significant number of episodes with reduced CKD-EPI (p < 0.001) as well as female (p = 0.005), being from Fortaleza or metropolitan region (p = 0.010) and being patients of white color (p < 0.001). Education is inversely associated with these episodes (p < 0.001) (Table 1).
Sample comorbidity profile and influence on the incidence of CDK-EPI episodes
There was a prevalence of Systemic Arterial Hypertension (SAH) as comorbidity, affecting 29 patients (38.7%), the classification of pre-obesity according to the Body Mass Index (BMI) was present in 30 patients (40.0%) and obesity I in 27 patients (36%). Non-dental follow-up was present in 62 patients (82.7%), the diagnosis of Multiple Myeloma (MM) affected about 33 (44.0%) and, concerning remission, chemotherapy as a type of treatment and not transplantation accounted for 63 (84.0%), 72 (96.0%) and 66 (88.0%) respectively (Table 2).
Table 2
Clinical and admission profile and its influences on the reduction of CKD-EPI in patients undergoing chemotherapy under analysis of renal function at the Hospital Universitário Walter Cantídio from 2012 to 2018.
|
|
CKD-EPI (n = 450)b
|
|
|
Sample
|
Normal
|
Reduced
|
p-value
|
Comorbidities
|
|
|
|
|
|
|
|
Systemic Arterial Hypertension
|
29
|
38.7%
|
33
|
15.4%
|
143*
|
60.6%
|
< 0.001
|
Diabetes Mellitus
|
12
|
16.0%
|
10
|
4.7%
|
62*
|
26.3%
|
< 0.001
|
Coronary disease
|
1
|
1.3%
|
0
|
0.0%
|
10*
|
4.2%
|
0.002
|
Chronic Obstructive Pulmonary Disease
|
1
|
1.3%
|
0
|
0.0%
|
4
|
1.7%
|
0.056
|
Others
|
12
|
16%
|
11
|
5.1%
|
75*
|
31.8%
|
< 0.001
|
Body mass index
|
|
|
|
|
|
|
|
Normal
|
5
|
6.7%
|
27*
|
12.6%
|
10
|
4.2%
|
< 0.001
|
Pre-obese
|
30
|
40.0%
|
90*
|
42.1%
|
59
|
25.0%
|
|
Obesity I
|
27
|
36.0%
|
51
|
23.8%
|
127*
|
53.8%
|
|
Obesity II
|
10
|
13.3%
|
27
|
12.6%
|
27
|
11.4%
|
|
Obesity III
|
3
|
4.0%
|
19
|
8.9%
|
13
|
5.5%
|
|
Dental care
|
|
|
|
|
|
|
|
No
|
62
|
82.7%
|
172
|
80.4%
|
171
|
72.5%
|
0.056
|
Yes
|
13
|
17.3%
|
42
|
19.6%
|
65
|
27.5%
|
|
Diagnosis
|
|
|
|
|
|
|
|
Multiple myeloma
|
33
|
44.0%
|
33
|
15.4%
|
183*
|
77.5%
|
< 0.001
|
Lymphoid leukemia
|
10
|
13.3%
|
58*
|
27.1%
|
7
|
3.0%
|
|
Myeloid leukemia
|
17
|
22.7%
|
91*
|
42.5%
|
38
|
16.1%
|
|
Lymphoma
|
15
|
20.0%
|
32*
|
15.0%
|
8
|
3.4%
|
|
Remission
|
|
|
|
|
|
|
|
No
|
63
|
84.0%
|
203*
|
94.9%
|
193
|
81.8%
|
< 0.001
|
Yes
|
12
|
16.0%
|
11
|
5.1%
|
43*
|
18.2%
|
|
Treatment type
|
|
|
|
|
|
|
|
CT
|
72
|
96.0%
|
200
|
93.5%
|
236*
|
100.0%
|
< 0.001
|
CT + RDT
|
3
|
4.0%
|
14*
|
6.5%
|
0
|
0.0%
|
|
Transplant
|
|
|
|
|
|
|
|
No
|
66
|
88.0%
|
205*
|
95.8%
|
199
|
84.3%
|
< 0.001
|
Yes
|
9
|
12.0%
|
9
|
4.2%
|
37*
|
15.7%
|
|
Medications in use
|
|
|
|
|
|
|
|
Acyclovir
|
33
|
44.0%
|
120*
|
56.1%
|
105
|
44.5%
|
0.014
|
Bactrim
|
41
|
54.7%
|
117
|
54.7%
|
177*
|
75.0%
|
< 0.001
|
Fluconazole
|
4
|
5.3%
|
30*
|
14.0%
|
12
|
5.1%
|
< 0.001
|
Levofloxacin
|
3
|
4.0%
|
25*
|
11.7%
|
12
|
5.1%
|
0.011
|
Others
|
32
|
42.7%
|
54
|
25.2%
|
143*
|
60.6%
|
< 0.001
|
Initial renal function
|
|
|
|
|
|
|
|
Normal
|
70
|
93.3%
|
207*
|
96.7%
|
208
|
88.1%
|
0.003
|
Acute renal failure
|
1
|
1.3%
|
2
|
0.9%
|
5*
|
2.1%
|
|
Chronic kidney disease
|
4
|
5.3%
|
5
|
2.3%
|
23*
|
9.7%
|
|
Hemodialysis
|
|
|
|
|
|
|
|
No
|
74
|
98.7%
|
214*
|
100.0%
|
231
|
97.9%
|
0.032
|
Yes
|
1
|
1.3%
|
0
|
0.0%
|
5*
|
2.1%
|
|
Place of application
|
|
|
|
|
|
|
|
Outpatient
|
67
|
89.3%
|
130
|
60.7%
|
212*
|
89.8%
|
< 0.001
|
Inpatient
|
8
|
10.7%
|
84*
|
39.3%
|
24
|
10.2%
|
|
Time to start treatment
|
|
|
|
|
|
|
|
Up to 40 days
|
37
|
49.3%
|
134*
|
62.6%
|
126
|
53.4%
|
0.048
|
> 40 days
|
38
|
50.7%
|
80
|
37.4%
|
110*
|
46.6%
|
|
Data expressed as absolute frequency and percentage. * p < 0.05, Fisher's exact test or Pearson's chi-square. aSample unit = patient; bSample unit = episodes of CDK-EPI assessment. |
According to the additional medications, Bactrim stood out among the others. Forty-one patients used it (54.7%). Thirty-three patients used acyclovir (44.0%). Thirty-two patients (42.7%) used other drugs (amitril, atenolol, omeprazole, metformin, simvastatin, atorvastatin, enalapril, aspirin, carvedilol, itraconazole, captopril, thalidomide, glibenclamide, propranolol, amlodipine, allopurinol, hydrochlorothiazide, gliclazide, Puran, nifedipine, furosemide, folic acid, Tazocin, dexamethasone, insulin, pregabalin, prednisone) (Table 2).
Almost the entire population had a normal initial renal function, 70 patients (93.3%), and 74 did not use hemodialysis (98.7). Regarding the place where the treatment was applied, the vast majority of patients were administered at the outpatient clinic, 67 (89.3%) and concerning the start of medications, part of the patients started after 40 days after diagnosis, representing 38 (50, 7%) (Table 2).
Regarding the clinical and admission profile of the patients, it was observed that SAH (p < 0.001), DM (p < 0.001), coronary disease (p = 0.002), other comorbidities (p < 0.001) of the most varied, grade I obesity (p < 0.001) are directly associated with a reduction in CKD-EPI. Although the lack of dental follow-up did not show statistical significance (p = 0.056), there is a trend when associated with a decrease in GFR (Table 2).
Patients diagnosed with multiple myeloma (p < 0.001) revealed more GFR reduction events as well as those who presented remission (p < 0.001), exclusive treatment with chemotherapy (p < 0.001) and transplantation (p < 0.001) (Table 2).
Acyclovir (p = 0.014), fluconazole (p = 0.001) and levofloxacin (p = 0.011) were inversely associated with a decrease in CKD-EPI whereas, the use of bactrim (p < 0.001) and other drugs (p < 0.001) showed a direct relationship with this change. According to renal function, patients who started treatment with AKI or CKD (p = 0.003) also had more episodes of reduced GFR as well as hemodialysis (p = 0.032) and progression to CKD (p < 0.001) (Table 2).
Patients who underwent treatment at the outpatient clinic (p < 0.001) were directly associated with renal dysfunction. It should be noted, however, that the sample studied consisted almost entirely of outpatients. There was also a higher number of dysfunctional episodes (p = 0.048) in patients who started treatment within 40 days after diagnosis (Table 2).
Therapeutic profile of the sample and influence of the scheme on the incidence of CDK-EPI episodes
The 75 patients participating in the research totaled 985 episodes of analysis (data collection), with a mean of 6.6 ± 6.8 and a median of 4 events per patient with a minimum and maximum of 1 to 46 events, respectively. Most patients underwent 1 to 2 cycles of CT, totaling 302 (30.7%) (Table 3).
Table 3
Clinical and admission profile of patients undergoing chemotherapy under analysis of renal function at Hospital Universitário Walter Cantídio from 2012 to 2018. Fortaleza / CE, Brazil. 2018.
|
n
|
%
|
Total number of episodes evaluated
|
985
|
100
|
Evaluation cycle
|
|
|
1st or 2nd cycle
|
302
|
30.7
|
3rd or 4th cycle
|
224
|
22.7
|
5th to 10th cycle
|
297
|
30.2
|
11th or higher
|
162
|
16.4
|
CKD-EPI (n = 450)
|
|
|
Normal
|
214
|
47.6
|
Reduced
|
236
|
52.4
|
GFR classification (n = 450)
|
|
|
Normal
|
212
|
47.1
|
Mild decrease
|
123
|
27.3
|
Mild to moderate
|
49
|
10.9
|
Moderate to severe
|
39
|
8.7
|
Severe decrease
|
21
|
4.7
|
Kidney failure
|
6
|
1.3
|
Data expressed as absolute frequency and percentage. * p < 0.05, Fisher's exact test or Pearson's chi-square. TGF = Glomerular filtration rate |
When the estimate of GFR was assessed using the CKD-EPI formula, a result of 450 analyzes was obtained, since not all patients had a creatinine value. Of these, 236 (52.4%) had reduced GFR and categorizing the GFR determined by the result of the CKD-EPI formula; it was found that 212 (47.1%) episodes were considered normal. This variable was used for association with the other sociodemographic, clinical, and therapeutic variables (Table 3).
Analyzing the therapeutic profile, it was possible to dichotomize groups: inversely associated with a reduction in GFR (Cyclophosphamide, Oncovin, Prednisone (COP) p = 0.004, Transretinoic Acid (ATRA) p < 0.001, Idarubicin p < 0.001, Daunorubicin p < 0.001, Filgrastim p = 0.003, Cancer and Leukemia Group B (CALGB) p < 0.001, Cytarabine p = 0.004, Procarbazine, Oncovin, Mecloretamine, Prednisone (POMP) p = 0.003, Imatinib p = 0.027, other drugs p = 0.003) and those directly related the decrease in GFR (Vidaza, Dexamethasone, Cyclophosphamide (VDC) p < 0.001, Zoledronate p < 0.001, Pamidronate p < 0.001, Talcidex p < 0.001) (Table 4).
Table 4
Influence of the therapeutic profile on the reduction of CKD-EPI in patients undergoing chemotherapy under analysis of renal function at Hospital Universitário Walter Cantídio from 2012 to 2018.
|
CKD-EPI (n = 450)
|
|
|
Normal
|
Reduced
|
p-Value
|
Cycle
|
|
|
|
|
|
1st or 2nd cycle
|
67
|
31.3%
|
91
|
38.6%
|
0.129
|
3rd or 4th cycle
|
41
|
19.2%
|
52
|
22.0%
|
|
5th to 10th cycle
|
66
|
30.8%
|
64
|
27.1%
|
|
11th or higher
|
40
|
18.7%
|
29
|
12.3%
|
|
Therapeutic schemes
|
|
|
|
|
|
Anti CD20
|
7
|
3.3%
|
2
|
0.8%
|
0.067
|
COP
|
10*
|
4.7%
|
1
|
0.4%
|
0.004
|
CHOP
|
1
|
0.5%
|
4
|
1.7%
|
0.215
|
Anti CD21
|
0
|
0.0%
|
1
|
0.4%
|
0.340
|
Anti CD22
|
0
|
0.0%
|
0
|
0.0%
|
1.000
|
ATRA
|
48*
|
22.4%
|
9
|
3.8%
|
< 0.001
|
Idarubicin
|
25*
|
11.7%
|
2
|
0.8%
|
< 0.001
|
Daunorubicin
|
10*
|
4.7%
|
0
|
0.0%
|
0.001
|
Mitoxantrone
|
0
|
0.0%
|
0
|
0.0%
|
1.000
|
Filgrastim
|
8*
|
3.7%
|
0
|
0.0%
|
0.003
|
CalgB
|
51*
|
23.8%
|
5
|
2.1%
|
< 0.001
|
Mabthera
|
1
|
0.5%
|
0
|
0.0%
|
0.293
|
Cytarabine
|
12*
|
5.6%
|
2
|
0.8%
|
0.004
|
Daunoblastin
|
1
|
0.5%
|
1
|
0.4%
|
0.945
|
VDC
|
5
|
2.3%
|
76*
|
32.2%
|
< 0.001
|
Zoledronate
|
12
|
5.6%
|
74*
|
31.4%
|
< 0.001
|
Pamidronate
|
4
|
1.9%
|
25*
|
10.6%
|
< 0.001
|
POMP
|
8*
|
3.7%
|
0
|
0.0%
|
0.003
|
Talcidex
|
9
|
4.2%
|
34*
|
14.4%
|
< 0.001
|
Nivolumab
|
0
|
0.0%
|
0
|
0.0%
|
1.000
|
Imatinib
|
11*
|
5.1%
|
3
|
1.3%
|
0.027
|
FLAG
|
13
|
6.1%
|
12
|
5.1%
|
0.647
|
Vidaza
|
0
|
0.0%
|
0
|
0.0%
|
1.000
|
Brentuximab
|
3
|
1.4%
|
0
|
0.0%
|
0.068
|
Other drugs **
|
22*
|
10.3%
|
8
|
3.4%
|
0.003
|
Data expressed as absolute frequency and percentage. *p < 0.05, Fisher's exact test or Pearson's chi-square. Sample unit = event. CHOP: Cyclophosphamide, Hydroxidoxorubicin, Oncovin, Prednisone. CalgB: Cancer and Leukemia Group B. POMP: Procarbazine, Oncovin, Mecloretamina, Prednisone. VDC: Velcade, Cyclophosphamide, and Dexamethasone. ATRA: Trans-retinoic acid. FLAG: Fludarabine, ARA-C, and Idarubicin. **Rituximab, GVD, ICE, ABVD, Hydroxyurea, Vesanoid, 6mercaptopurine, methotrexate, MADIT, PVAB, GVM, FC Lite, FCR, Hipercvad cycle A. |
When the multivariate analysis of the variables that showed significant relevance of the sociodemographic and clinical admission aspects was performed, it was found that being female increased the chance of episodes with a reduction in the CKD-EPI index by 18.75 times. Also, the diagnosis of MM increased this prevalence by 4,111.01 times, as well as the initiation of treatment within 40 days after the diagnosis increased the risk by 103.25 times (Table 5).
Table 5
Multivariate and multilevel analysis of sociodemographic, clinical admissions, and pharmacotherapies modifying the prevalence of CKD-EPI and multilevel analysis of independent factors associated with increased prevalence of CKD-EPI in patients undergoing chemotherapy under analysis of renal function at Walter Cantídio University Hospital in the period from 2012 to 2018.
|
Multivariate
|
|
Multilevel
|
|
p-Value
|
Adjusted OR
|
|
p-Value
|
Adjusted OR
|
Reduced CKD-EPI
|
|
|
|
|
|
Age (> 50)
|
0.972
|
-
|
|
-
|
-
|
Sex (Female)
|
0.002
|
18.75 (2.83-124.01)
|
|
0.010
|
2.26 (1.12–4.21)
|
Race (White)
|
1.000
|
-
|
|
-
|
-
|
Education (Illiterate / Elementary)
|
0.963
|
-
|
|
-
|
-
|
Place of birth (Fortaleza / metropolitan area)
|
0.973
|
-
|
|
-
|
-
|
SAH (Yes)
|
0.980
|
-
|
|
-
|
-
|
Diabetes Mellitus (Yes)
|
0.988
|
-
|
|
-
|
-
|
CD (Yes)
|
0.981
|
-
|
|
-
|
-
|
Others (Yes)
|
1.000
|
-
|
|
-
|
-
|
BMI (Obese)
|
0.084
|
-
|
|
-
|
-
|
Diagnosis (Multiple myeloma)
|
0.008
|
4111.01 (9.06–1.865.992)
|
|
< 0.001
|
5.75 (2.86–11.53)
|
Remission (Yes)
|
0.997
|
-
|
|
-
|
-
|
Treatment type (CT)
|
0.989
|
-
|
|
-
|
-
|
Transplant (Yes)
|
0.988
|
-
|
|
-
|
-
|
Initial kidney function (Normal)
|
0.932
|
-
|
|
-
|
-
|
Hemodialysis (Yes)
|
1.000
|
-
|
|
-
|
-
|
Evolution (Normal)
|
1.000
|
-
|
|
-
|
-
|
Application location (Inpatient)
|
0.060
|
-
|
|
-
|
-
|
Time to start treatment (Up to 40 days)
|
0.005
|
103.25 (4.16–2.559.69)
|
|
0.059
|
-
|
COP
|
0.026
|
0.09 (0.01–0.75)
|
|
0.116
|
-
|
ATRA
|
0.122
|
-
|
|
-
|
-
|
Idarubicin
|
0.032
|
0.12 (0.02–0.84)
|
|
0.134
|
-
|
Daunorubicin
|
0.988
|
-
|
|
-
|
-
|
Filgastrin
|
0.989
|
-
|
|
-
|
-
|
CalgB
|
< 0.001
|
0.09 (0.03–0.26)
|
|
0.005
|
0.23 (0.08–0.64)
|
Cytarabine
|
0.765
|
-
|
|
-
|
-
|
VDC
|
< 0.001
|
11.7 (4.09–33.85)
|
|
< 0.001
|
10.64 (3.78–29.86)
|
Zoledronate
|
< 0.001
|
4.42 (1.97–9.92)
|
|
0.006
|
3.20 (1.41–7.29)
|
Pamidronate
|
0.012
|
4.60 (1.40-15.12)
|
|
0.032
|
3.86 (1.12–13.32)
|
POMP
|
0.989
|
-
|
|
-
|
-
|
Talcidity
|
0.052
|
-
|
|
-
|
-
|
Imatinib
|
0.136
|
-
|
|
-
|
-
|
Granulokine
|
1.000
|
-
|
|
-
|
-
|
Others
|
0.025
|
0.32 (0.12–0.87)
|
|
0.21
|
-
|
* p < 0.05, multinomial logistic regression. Sample unit = event. SAH: Systemic Arterial Hypertension; CD: Coronary disease; BMI: Body Mass Index; CT: Chemotherapy; COP: Cyclophosphamide, Oncovin, Prednisone. ATRA: Transretinoic acid. CalgB: Cancer and Leukemia Group B. VDC: Velcade, Cyclophosphamide, Dexamethasone. POMP: Procarbazine, Oncovin, Mecloretamina, Prednisone. |
When performing the same procedure with the variables involved in the treatment, it was found that the use of COP, Idarubicin, CalgB, and others were inversely associated, reducing by 0.09, 0.12, 0.09 and 0.32 times, in this order, the prevalence of episodes with decreased CKD-EPI, independently of the others. However, the use of VDC, Zoledronate, Pamidronate increased, respectively, 11.77, 4.42, 4.60 the chances of occurring the renal dysfunction event (Table 5).
Finally, another analysis of the variables described above was made, highlighting that, independently, the female gender and the diagnosis of MM are associated with a greater probability of occurring episodes with renal dysfunction in 2.26 and 5.75 times, respectively. This fact also happened with the use of Vidaza, Zoledronate, and Pamidronate, increasing the chances by 10.64, 3.20, and 3.86 times, respectively. On the other hand, the use of CalgB was inversely associated with the occurrence of episodes with low GFR, reduced by 0.23 times (Table 5).