Analisis exploratorio de los datos

library(readxl)
library(summarytools)
library(dplyr)

BASE <- read_excel("Base NMR-1_23.08.26.xlsx")
BASE <- BASE %>% 
  mutate(across(
    matches("fecha", ignore.case = TRUE), 
    ~ as.Date(., format = "%d/%m/%Y")
  ))

print(dfSummary(BASE[ , -c(1,2,3)]), method = "render")

Data Frame Summary

BASE

Dimensions: 44 x 145
Duplicates: 0
No Variable Stats / Values Freqs (% of Valid) Graph Valid Missing
1 EPS [character]
1. ALIANSALUD
2. CAFAM
3. COLMEDICA
4. COMPENSAR
5. NUEVA EPS
10(22.7%)
2(4.5%)
1(2.3%)
27(61.4%)
4(9.1%)
 44 (100.0%) 0 (0.0%)
2 ESTRATO [numeric]
Mean (sd) : 2.8 (1.1)
min ≤ med ≤ max:
1 ≤ 3 ≤ 5
IQR (CV) : 1 (0.4)
1:6(16.2%)
2:5(13.5%)
3:20(54.1%)
4:3(8.1%)
5:3(8.1%)
 37 (84.1%) 7 (15.9%)
3 SEXO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:36(81.8%)
1:8(18.2%)
 44 (100.0%) 0 (0.0%)
4 FECHA NACIMIENTO [Date]
min : 1935-05-02
med : 1952-11-15
max : 1991-05-14
range : 56y 0m 12d
 44 distinct values 44 (100.0%) 0 (0.0%)
5 TALLA (M) [numeric]
Mean (sd) : 1.6 (0.1)
min ≤ med ≤ max:
1.4 ≤ 1.6 ≤ 1.8
IQR (CV) : 0.2 (0.1)
 26 distinct values 44 (100.0%) 0 (0.0%)
6 PESO (KG) [numeric]
Mean (sd) : 59.5 (11.7)
min ≤ med ≤ max:
37 ≤ 62 ≤ 86
IQR (CV) : 14.5 (0.2)
 28 distinct values 44 (100.0%) 0 (0.0%)
7 IMC [numeric]
Mean (sd) : 24.1 (4.4)
min ≤ med ≤ max:
15.8 ≤ 23.9 ≤ 38.2
IQR (CV) : 5.2 (0.2)
 44 distinct values 44 (100.0%) 0 (0.0%)
8 GLAUCOMA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
9 HPB [numeric]
Min : 0
Mean : 0
Max : 1
0:42(95.5%)
1:2(4.5%)
 44 (100.0%) 0 (0.0%)
10 TUBERCULOSIS [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
11 LES [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
12 DESPRENDIMIENTO RETI. [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
13 ESTEATOSIS [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
14 VALVULOPATIA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
15 MENINGIOMA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
16 VASCULITIS [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
17 ACV [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
18 ADENOMA HIPOFISIARIO [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
19 MIOMATOSIS UTERINA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
20 ENFERMEDAD DIVERTICULAR [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
21 COLON IRRITABLE [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
22 CARDIOPATÍA HIPERTENSIVA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
23 DEPRESIÓN [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
24 CEFALEA PRIMARIA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
25 EPILEPSIA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(95.5%)
1:2(4.5%)
 44 (100.0%) 0 (0.0%)
26 HIPOTIROIDISMO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:34(77.3%)
1:10(22.7%)
 44 (100.0%) 0 (0.0%)
27 HT PULMONAR [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
28 SD GILBERT [numeric]
Min : 0
Mean : 0.1
Max : 1
0:41(93.2%)
1:3(6.8%)
 44 (100.0%) 0 (0.0%)
29 SAHOS [numeric]
Min : 0
Mean : 0.1
Max : 1
0:40(90.9%)
1:4(9.1%)
 44 (100.0%) 0 (0.0%)
30 EPOC [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
31 CARDIOPATÍA ISQUÉMICA [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
32 ARRITMIAS [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
33 ETEV [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(88.6%)
1:5(11.4%)
 44 (100.0%) 0 (0.0%)
34 VÉRTIGO [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
35 CONSUMO PSICOACTIVOS [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
36 TRASTORNO ADAPTATIVO [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
37 CAVERNOMATOSIS MÚLTIPLE [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
38 HIPERTENSIÓN [numeric]
Min : 0
Mean : 0.4
Max : 1
0:25(56.8%)
1:19(43.2%)
 44 (100.0%) 0 (0.0%)
39 DISLIPIDEMIA [numeric]
Min : 0
Mean : 0.1
Max : 1
0:40(90.9%)
1:4(9.1%)
 44 (100.0%) 0 (0.0%)
40 PREDIABETES [numeric]
Min : 0
Mean : 0
Max : 1
0:42(95.5%)
1:2(4.5%)
 44 (100.0%) 0 (0.0%)
41 DIABETES [numeric]
Min : 0
Mean : 0.1
Max : 1
0:38(86.4%)
1:6(13.6%)
 44 (100.0%) 0 (0.0%)
42 SOBREPESO [numeric]
Min : 0
Mean : 0
Max : 1
0:42(95.5%)
1:2(4.5%)
 44 (100.0%) 0 (0.0%)
43 OBESIDAD [numeric]
Min : 0
Mean : 0
Max : 1
0:42(95.5%)
1:2(4.5%)
 44 (100.0%) 0 (0.0%)
44 ARTROSIS [numeric]
Min : 0
Mean : 0.1
Max : 1
0:41(93.2%)
1:3(6.8%)
 44 (100.0%) 0 (0.0%)
45 OSTEOPOROSIS [numeric]
Min : 0
Mean : 0.2
Max : 1
0:37(84.1%)
1:7(15.9%)
 44 (100.0%) 0 (0.0%)
46 HIPERPLASIA ENDOMETRIAL [numeric]
Min : 0
Mean : 0
Max : 1
0:43(97.7%)
1:1(2.3%)
 44 (100.0%) 0 (0.0%)
47 Charlson [numeric]
Mean (sd) : 8.9 (1.8)
min ≤ med ≤ max:
5 ≤ 9 ≤ 15
IQR (CV) : 2 (0.2)
5:1(2.3%)
6:2(4.5%)
7:4(9.1%)
8:9(20.5%)
9:16(36.4%)
10:8(18.2%)
11:2(4.5%)
14:1(2.3%)
15:1(2.3%)
 44 (100.0%) 0 (0.0%)
48 Otra neoplasia concomitante [numeric]
Min : 0
Mean : 0.2
Max : 1
0:37(84.1%)
1:7(15.9%)
 44 (100.0%) 0 (0.0%)
49 SOLO SI NEOPLASIA [character]
1. Ca ca.l a.l - Ca endometr
2. Ca Cromófobo de riñón 201
3. Ca de mama ductal
4. Ca papilar tiroides, CBC
5. Ca seroso de endometrio
6. Leucemia linfocítica crón
7. Linfoma cutáneo
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
 7 (15.9%) 37 (84.1%)
50 ANTECEDENTE TABAQUISMO [numeric]
Min : 0
Mean : 0.3
Max : 1
0:32(72.7%)
1:12(27.3%)
 44 (100.0%) 0 (0.0%)
51 ANTECEDENTE FAMILIAR DE CANCER [numeric]
Min : 0
Mean : 0.3
Max : 1
0:29(65.9%)
1:15(34.1%)
 44 (100.0%) 0 (0.0%)
52 ECOG [numeric]
Mean (sd) : 1.1 (0.8)
min ≤ med ≤ max:
0 ≤ 1 ≤ 3
IQR (CV) : 0 (0.7)
0:9(20.5%)
1:25(56.8%)
2:7(15.9%)
3:3(6.8%)
 44 (100.0%) 0 (0.0%)
53 KARNOSFKY [numeric]
Mean (sd) : 84.5 (15.6)
min ≤ med ≤ max:
40 ≤ 90 ≤ 100
IQR (CV) : 2.5 (0.2)
40:1(2.3%)
50:3(6.8%)
60:3(6.8%)
70:2(4.5%)
80:2(4.5%)
90:25(56.8%)
100:8(18.2%)
 44 (100.0%) 0 (0.0%)
54 VALORACION GERIATRICA INTEGRAL [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(88.6%)
1:5(11.4%)
 44 (100.0%) 0 (0.0%)
55 DIAGNOSTICO [numeric]
Mean (sd) : 1.2 (0.6)
min ≤ med ≤ max:
1 ≤ 1 ≤ 3
IQR (CV) : 0 (0.5)
1:38(86.4%)
2:3(6.8%)
3:3(6.8%)
 44 (100.0%) 0 (0.0%)
56 ESTADIO [character]
1. IA3
2. IB
3. IIA
4. IIIa
5. IIIA
6. IIIB
7. IV
8. IVa
9. IVA
10. IVB
1(2.3%)
2(4.5%)
2(4.5%)
1(2.3%)
1(2.3%)
3(6.8%)
28(63.6%)
2(4.5%)
2(4.5%)
2(4.5%)
 44 (100.0%) 0 (0.0%)
57 T [character]
1. 1
2. 1c
3. 1C
4. 2
5. 2A
6. 2B
7. 3
8. 3A
9. 4
10. x
11. X
1(2.3%)
1(2.3%)
1(2.3%)
7(15.9%)
2(4.5%)
3(6.8%)
6(13.6%)
1(2.3%)
11(25.0%)
1(2.3%)
10(22.7%)
 44 (100.0%) 0 (0.0%)
58 N [character]
1. 0
2. 1
3. 2
4. 2A
5. 3
6. X
7(15.9%)
4(9.1%)
6(13.6%)
1(2.3%)
9(20.5%)
17(38.6%)
 44 (100.0%) 0 (0.0%)
59 M [character]
1. 0
2. 1
3. 1C
11(25.0%)
32(72.7%)
1(2.3%)
 44 (100.0%) 0 (0.0%)
60 PLEURA [numeric]
Min : 0
Mean : 0.2
Max : 1
0:34(77.3%)
1:10(22.7%)
 44 (100.0%) 0 (0.0%)
61 MET HEPATICA [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(88.6%)
1:5(11.4%)
 44 (100.0%) 0 (0.0%)
62 MET GANGLIONAR [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(88.6%)
1:5(11.4%)
 44 (100.0%) 0 (0.0%)
63 MET SNC [numeric]
Min : 0
Mean : 0.2
Max : 1
0:34(77.3%)
1:10(22.7%)
 44 (100.0%) 0 (0.0%)
64 METS HUESO [numeric]
Min : 0
Mean : 0.3
Max : 1
0:29(65.9%)
1:15(34.1%)
 44 (100.0%) 0 (0.0%)
65 MET PULMON CONTRALATERAL [numeric]
Min : 0
Mean : 0.4
Max : 1
0:27(61.4%)
1:17(38.6%)
 44 (100.0%) 0 (0.0%)
66 TRATAMIENTO DE METASTASIS 0=Cirugía, 1=Radioterapia, 2= Ninguno [character]
1. .
2. 0
3. 1
4. 2
6(13.6%)
2(4.5%)
15(34.1%)
21(47.7%)
 44 (100.0%) 0 (0.0%)
67 DIAGNÓSTICO HISTOLÓGICO [numeric] 1 distinct value
2:44(100.0%)
 44 (100.0%) 0 (0.0%)
68 GRADO DE DIFERENCIACIÓN [numeric]
Mean (sd) : 2.3 (0.6)
min ≤ med ≤ max:
1 ≤ 2 ≤ 3
IQR (CV) : 1 (0.3)
1:2(6.7%)
2:17(56.7%)
3:11(36.7%)
 30 (68.2%) 14 (31.8%)
69 VARIANTE HISTOPATOLÓGICA [character]
1. Adenoescamoso
2. NSCLC
3. NSCLC (transformación a S
2(4.5%)
41(93.2%)
1(2.3%)
 44 (100.0%) 0 (0.0%)
70 VARIANTES DE ADENOCARCINOMA [character]
1. Variante Aci.r
2. Aci.r
3. Adenoescamoso
4. Aci.r 40% papilar 30% lep
5. Aci.r mucinoso
6. adenocarcinoma metastasic
7. Carcinoma de celula grand
8. Carcinoma de patrón lepíd
9. Célula grande
10. Celula no pequeña
[ 7 others ]
7(28.0%)
2(8.0%)
2(8.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
7(28.0%)
 25 (56.8%) 19 (43.2%)
71 PERFIL MUTACIONAL [character]
1. EGFR (no se conoce cual e
2. EGFR Del exon 19
3. EGFR deleción de exón 19
4. EGFR exon 20 L858R exon 2
5. EGFR exon 21
6. EGFR exón 21
1(2.3%)
6(13.6%)
24(54.5%)
1(2.3%)
1(2.3%)
11(25.0%)
 44 (100.0%) 0 (0.0%)
72 PDL-1 [character]
1. < 1
2. <1
3. >10
4. 0
5. 1
6. 10
7. 5
8. 95
12(35.3%)
4(11.8%)
1(2.9%)
10(29.4%)
2(5.9%)
2(5.9%)
2(5.9%)
1(2.9%)
 34 (77.3%) 10 (22.7%)
73 TMB (mut/megaPb) [numeric]
Min : 0.6
Mean : 14.4
Max : 28.2
 2 distinct values 2 (4.5%) 42 (95.5%)
74 MEDIASTINOSCOPIA DX PREVIA A CIRUGIA: 1.SI 0.NO [numeric]
Mean (sd) : 0.3 (0.6)
min ≤ med ≤ max:
0 ≤ 0 ≤ 2
IQR (CV) : 0 (2)
0:20(76.9%)
1:4(15.4%)
2:2(7.7%)
 26 (59.1%) 18 (40.9%)
75 TIPO DE BIOPSIA [character]
1. BIOPSIA DE PULMON
2. BIOPSIA PLEURAL
3. BX PERCUTANEA
4. EBUS
5. EXCISIO.L
6. LOBECTOMIA
7. PLEURA PARIETAL
8. PULMO.R
9. PULMÓN PERCUTÁNEA
10. PULMÓN TRANSBRONQUIAL
1(3.1%)
6(18.8%)
1(3.1%)
1(3.1%)
5(15.6%)
1(3.1%)
1(3.1%)
1(3.1%)
13(40.6%)
2(6.2%)
 32 (72.7%) 12 (27.3%)
76 BIOPSIA POR TAC 1: SI 0: NO [numeric]
Min : 0
Mean : 0.6
Max : 1
0:11(40.7%)
1:16(59.3%)
 27 (61.4%) 17 (38.6%)
77 Broncoscopia 1, SI 0, NO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:22(75.9%)
1:7(24.1%)
 29 (65.9%) 15 (34.1%)
78 EBUS-EUS DIAGNÓSTICO ENFERMEDAD MEDIASTI.L PREVIO A CIRUGÍA: 1:SI 0:NO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:29(82.9%)
1:6(17.1%)
 35 (79.5%) 9 (20.5%)
79 FECHA DE DIAGNOSTICO (FECHA DE BIOPSIA) [Date]
min : 2006-01-01
med : 2022-12-23
max : 2024-11-29
range : 18y 10m 28d
 42 distinct values 44 (100.0%) 0 (0.0%)
80 INGRESA A LA UFC DE PULMÓN [numeric]
Min : 0
Mean : 1
Max : 1
0:1(2.3%)
1:43(97.7%)
 44 (100.0%) 0 (0.0%)
81 FECHA DE INGRESO [Date]
min : 2019-03-11
med : 2023-07-12
max : 2025-02-10
range : 5y 10m 30d
 43 distinct values 43 (97.7%) 1 (2.3%)
82 FECHA DE 1ª VALORACION HUSI [Date]
min : 2019-02-15
med : 2023-03-14
max : 2024-12-23
range : 5y 10m 8d
 43 distinct values 44 (100.0%) 0 (0.0%)
83 ESPECIALIDAD DE INGRESO [character]
1. CIRUGIA DE TORAX
2. CUIDADOS PALIATIVOS
3. NEUMOLOGIA
4. ONCOLOGIA CLINICA
5. ONCOLOGIA CLINICA
5(11.4%)
1(2.3%)
3(6.8%)
1(2.3%)
34(77.3%)
 44 (100.0%) 0 (0.0%)
84 VIA DE INGRESO 1: AMBULATORIO 2: HOSPITALIZADO [numeric]
Min : 1
Mean : 1
Max : 2
1:42(95.5%)
2:2(4.5%)
 44 (100.0%) 0 (0.0%)
85 FECHA VALORACIÓN ONCOLOGÍA [Date] 1. 2023-11-08
1(100.0%)
 1 (2.3%) 43 (97.7%)
86 FECHA DE ORDEN JUNTA MEDICA [Date] 1. 2023-08-25
1(100.0%)
 1 (2.3%) 43 (97.7%)
87 FECHA PACIENTE COMPLETA ESTUDIOS POR EPS / IPS [Date]
min : 2019-03-07
med : 2023-06-09
max : 2025-01-16
range : 5y 10m 9d
 41 distinct values 42 (95.5%) 2 (4.5%)
88 FECHA DE JUNTA MEDICA [Date]
min : 2019-03-11
med : 2023-04-17
max : 2025-02-10
range : 5y 10m 30d
 41 distinct values 43 (97.7%) 1 (2.3%)
89 VALORACIÓN POR GRUPO DE SOPORTE CUIDADO PALIATIVO [POSIXct, POSIXt]
min : 2019-03-05
med : 2023-06-19
max : 2025-02-25
range : 5y 11m 20d
 40 distinct values 40 (90.9%) 4 (9.1%)
90 INDICACIÓN QUIRÚRGICA INICIAL [character]
1. CURATIVA
2. DIAGNÓSTICA
3. MEDIASTINOSCOPIA
4. NO APLICA
5. PALIATIVA
6. PELURECTOMIA PARIETAL
7. TERAPÉUTICA
1(5.3%)
6(31.6%)
1(5.3%)
6(31.6%)
1(5.3%)
1(5.3%)
3(15.8%)
 19 (43.2%) 25 (56.8%)
91 PROCEDIMIENTO QUIRÚRGICO [character]
1. 1. NINGU.
2. 11.RESECCIÓN TUMOR DEL ME
3. CUÑA
4. LOBECTOMIA
5. LOBECTOMÍA + VG
6. MEDIASTINOSCOPIA + VG
7. PLEURECTOMIA PARITETAL
8. PLEURECTOMIA POR TORACOSC
7(35.0%)
1(5.0%)
1(5.0%)
4(20.0%)
2(10.0%)
3(15.0%)
1(5.0%)
1(5.0%)
 20 (45.5%) 24 (54.5%)
92 BORDES COMPROMETIDOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [character]
1. LIBRES
2. NO
3. SI
4(57.1%)
2(28.6%)
1(14.3%)
 7 (15.9%) 37 (84.1%)
93 GANGLIOS RESECADOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [character]
1. 10
2. 13
3. 16
4. 7
5. 8
6. VACIAMIENTO N1 Y N2
1(12.5%)
1(12.5%)
2(25.0%)
1(12.5%)
2(25.0%)
1(12.5%)
 8 (18.2%) 36 (81.8%)
94 GANGLIOS COMPROMETIDOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [numeric]
Min : 0
Mean : 1.2
Max : 5
0:6(75.0%)
5:2(25.0%)
 8 (18.2%) 36 (81.8%)
95 FECHA DE ORDEN DE CIRUGÍA [Date] 1. 2023-06-06
1(100.0%)
 1 (2.3%) 43 (97.7%)
96 FECHA VALORACIÓN DE ANESTESIA [Date]
1. 1970-01-01
2. 2076-01-03
3. 2092-03-02
4. 2092-05-21
5. 2092-09-23
6. 2093-04-28
7. 2093-05-03
8. 2093-09-15
9. 2093-12-28
15(65.2%)
1(4.3%)
1(4.3%)
1(4.3%)
1(4.3%)
1(4.3%)
1(4.3%)
1(4.3%)
1(4.3%)
 23 (52.3%) 21 (47.7%)
97 FECHA DE CIRUGIA [Date]
min : 1970-01-01
med : 1970-01-01
max : 2094-01-19
range : 124y 0m 18d
 13 distinct values 27 (61.4%) 17 (38.6%)
98 MODALIDAD DE TRATAMIENTO ORDE.DO [character]
1. TERAPIA DIRIGIDA
2. iTK
3. QUIMIOTERAPIA
4. TERAPIA DIRIGIDA - QUIMIO
5. QUMIOTERAPIA
6. CIRUGIA
7. CIRUGÍA Y QUIMIOTERAPIA
8. ITK
9. PALIATIVO
10. QUIMIOTERAPIA
ITK
[ 5 others ]
14(31.8%)
6(13.6%)
5(11.4%)
5(11.4%)
3(6.8%)
2(4.5%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
5(11.4%)
 44 (100.0%) 0 (0.0%)
99 ESQUEMA DE QUIMIOTERAPIA [character]
1. CARBOPLATINO PACLITAXEL
2. CARBOPLATINO PEMETREXED
3. CISPLATINO PEMETREXED
4. NO APLICA
5. PENDIENTE
1(2.3%)
15(34.1%)
3(6.8%)
24(54.5%)
1(2.3%)
 44 (100.0%) 0 (0.0%)
100 FECHA DE ORDEN DE QUIMIOTERAPIA [Date]
All NA's
 0 (0.0%) 44 (100.0%)
101 FECHA INICIO QUIMIOTERAPIA [Date]
min : 1970-01-01
med : 2091-01-28
max : 2095-02-01
range : 125y 1m 0d
 21 distinct values 34 (77.3%) 10 (22.7%)
102 iTK ORDENADO [character]
1. ERLOTINIB
2. OSIMERTINIB
2(4.5%)
42(95.5%)
 44 (100.0%) 0 (0.0%)
103 FECHA DE ORDEN DE iTK [Date] 1. 2023-10-03
1(100.0%)
 1 (2.3%) 43 (97.7%)
104 FECHA INICIO iTK [Date]
min : 2019-03-26
med : 2023-07-14
max : 2025-01-29
range : 5y 10m 3d
 41 distinct values 44 (100.0%) 0 (0.0%)
105 RADIOTERAPIA [character]
1. NO
2. SI
3(14.3%)
18(85.7%)
 21 (47.7%) 23 (52.3%)
106 DOSIS RT ADMINISTRADA [character]
1. 20
2. 2 Gy
3. 20 gy
4. 20 Gy
5. 2000/400 cGy
6. 25 Gy
7. 25 LUEGO 30 GY
8. 30
9. 3000
10. 3000 GY
[ 8 others ]
2(10.5%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
1(5.3%)
8(42.1%)
 19 (43.2%) 25 (56.8%)
107 TIPO DE RADIOTERAPIA [character]
1. 3DCRT
2. IMRT
3. IMRT/HOLOCRANEA.
4. NO APLICA
5. Radiocirugía - GammaKnife
6. RADIOCIRUGIA FOTONES
7. SBRT
1(5.3%)
6(31.6%)
1(5.3%)
2(10.5%)
1(5.3%)
1(5.3%)
7(36.8%)
 19 (43.2%) 25 (56.8%)
108 RADIOTERAPIA HUESO [numeric]
Min : 0
Mean : 0.4
Max : 1
0:15(57.7%)
1:11(42.3%)
 26 (59.1%) 18 (40.9%)
109 RADIOTERAPIA SNC [numeric]
Min : 0
Mean : 0.2
Max : 1
0:20(76.9%)
1:6(23.1%)
 26 (59.1%) 18 (40.9%)
110 RADIOTERAPIA PULMON [numeric]
Min : 0
Mean : 0.2
Max : 1
0:21(80.8%)
1:5(19.2%)
 26 (59.1%) 18 (40.9%)
111 FECHA DE VALORACIÓN DE RADIOTERAPIA [Date]
min : 1970-01-01
med : 2091-09-13
max : 2094-10-12
range : 124y 9m 11d
 17 distinct values 24 (54.5%) 20 (45.5%)
112 FECHA DE INICIO DE RADIOTERAPIA [Date]
All NA's
 0 (0.0%) 44 (100.0%)
113 INTENCIÓN INICIAL DE TRATAMIENTO [character]
1. CURATIVO
2. PALIATIVO
3(6.8%)
41(93.2%)
 44 (100.0%) 0 (0.0%)
114 TRATAMIENTO INICIAL ORDENADO [character]
1. iTK
2. QUIMIOTERAPIA
3. ITK
4. CIRUGIA
5. CIRUGÍA
6. RADIOTERAPIA MET + iTK
7. CIRUGÍA DE RESECCIÓN
8. PALIATIVO
9. QUIMIOTERAPIA + iTK
10. QUIMIOTERAPIA
iTK
[ 3 others ]
19(43.2%)
8(18.2%)
4(9.1%)
2(4.5%)
2(4.5%)
2(4.5%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
3(6.8%)
 44 (100.0%) 0 (0.0%)
115 TRATAMIENTO ACTUAL [character]
1. CARBO/PEMETREXED
2. FLAURA-2
3. OSIMERTINIB
4. OSIMERTINIB - PEMETREXED
5. OSIMERTINIB
+ PEMETRE
6. OSIMERTINIB
CIRUGIA
Q
1(2.3%)
2(4.5%)
38(86.4%)
1(2.3%)
1(2.3%)
1(2.3%)
 44 (100.0%) 0 (0.0%)
116 FECHA DE INICIO DE TRATAMIENTO CX-QXT-RXT-INMUNO [Date]
min : 2006-01-01
med : 2023-07-17
max : 2025-01-30
range : 19y 0m 29d
 44 distinct values 44 (100.0%) 0 (0.0%)
117 OPORTUNIDAD DE JUNTA MEDICA [numeric]
Mean (sd) : 25.3 (53.7)
min ≤ med ≤ max:
-262 ≤ 22 ≤ 132
IQR (CV) : 39.5 (2.1)
 34 distinct values 43 (97.7%) 1 (2.3%)
118 OPORTUNIDAD DE VALORACIÒN PREANESTESIA [numeric]
Mean (sd) : 1.7 (5.1)
min ≤ med ≤ max:
0 ≤ 0 ≤ 23
IQR (CV) : 0 (2.9)
0:36(85.7%)
1:1(2.4%)
9:2(4.8%)
15:1(2.4%)
16:1(2.4%)
23:1(2.4%)
 42 (95.5%) 2 (4.5%)
119 OPORTUNIDAD DE CIRUGÍA [numeric]
Mean (sd) : 4206 (13096.7)
min ≤ med ≤ max:
0 ≤ 0 ≤ 44552
IQR (CV) : 0 (3.1)
 11 distinct values 42 (95.5%) 2 (4.5%)
120 OPORTUNIDAD DE INICIO QXT [numeric]
Mean (sd) : 6.2 (8.1)
min ≤ med ≤ max:
0 ≤ 0 ≤ 29
IQR (CV) : 13 (1.3)
 13 distinct values 42 (95.5%) 2 (4.5%)
121 OPORTUNIDAD DE INICIO TRATAMIENTO DIRIGIDO [numeric]
Mean (sd) : 1010.6 (6573.2)
min ≤ med ≤ max:
-239 ≤ 13 ≤ 43111
IQR (CV) : 13 (6.5)
 28 distinct values 43 (97.7%) 1 (2.3%)
122 OPORTUNIDAD DE INICIO RXT [numeric]
Mean (sd) : 1070.6 (6858.5)
min ≤ med ≤ max:
0 ≤ 0 ≤ 44460
IQR (CV) : 18.5 (6.4)
 17 distinct values 42 (95.5%) 2 (4.5%)
123 OPORTUNIDAD DE INICIO DE TRATAMIENTO DESDE EL DIAGNÓSTICO POR PATOLOGÍA [numeric]
Mean (sd) : 82 (95)
min ≤ med ≤ max:
-13 ≤ 66 ≤ 565
IQR (CV) : 53.8 (1.2)
 39 distinct values 44 (100.0%) 0 (0.0%)
124 OPORTUNIDAD DE INICIO DESDE LA PRIMERA ATENCIÓN DEL HUSI [numeric]
Mean (sd) : -59.2 (781.6)
min ≤ med ≤ max:
-5015 ≤ 41 ≤ 542
IQR (CV) : 69.5 (-13.2)
 39 distinct values 43 (97.7%) 1 (2.3%)
125 FECHA DE MUERTE [Date]
1. 2024-01-26
2. 2024-02-19
3. 2024-05-07
4. 2024-05-10
5. 2024-07-02
6. 2024-07-08
7. 2024-07-15
8. 2024-12-09
9. 2025-01-31
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
2(20.0%)
1(10.0%)
1(10.0%)
1(10.0%)
 10 (22.7%) 34 (77.3%)
126 CAUSAS DE EGRESO [character] 1. MUERTE
10(100.0%)
 10 (22.7%) 34 (77.3%)
127 # DE DÍAS PCTE VIVO DESDE LA PATOLOGÍA [numeric]
Mean (sd) : 942.7 (1003.3)
min ≤ med ≤ max:
129 ≤ 668.5 ≤ 6594
IQR (CV) : 630.8 (1.1)
 44 distinct values 44 (100.0%) 0 (0.0%)
128 # DE DÍAS PACTE VIVO DESDE INICIO DE TRATAMIENTO [numeric]
Mean (sd) : 860.7 (1016.7)
min ≤ med ≤ max:
102 ≤ 596.5 ≤ 6594
IQR (CV) : 537 (1.2)
 42 distinct values 44 (100.0%) 0 (0.0%)
129 EDAD EN AÑOS (FALLECE) [numeric]
Mean (sd) : 71.6 (11)
min ≤ med ≤ max:
49 ≤ 73 ≤ 89
IQR (CV) : 12 (0.2)
 12 distinct values 13 (29.5%) 31 (70.5%)
130 FECHA DE DIAGNÓSTICO POR PATOLOGÍA [Date]
min : 2006-01-01
med : 2023-01-24
max : 2024-11-29
range : 18y 10m 28d
 43 distinct values 44 (100.0%) 0 (0.0%)
131 FECHA DE PROGRESIÓN [Date]
min : 2020-11-01
med : 2024-01-04
max : 2025-01-28
range : 4y 2m 27d
 12 distinct values 12 (27.3%) 32 (72.7%)
132 TIPO DE PROGRESIÓN 0=OLIGOPROGRESIÓN, 1=PROGRESIÓN [numeric]
Min : 0
Mean : 0.7
Max : 1
0:3(27.3%)
1:8(72.7%)
 11 (25.0%) 33 (75.0%)
133 TRATAMIENTO POSTERIOR A PROGRESIÓN [character]
1. Carboplatino/Etoposido/Du
2. FLAURA-2
3. OSIMERTINIB
4. QT
5. QT+INMUNO
6. QUIMIOTERAPIA
7. Radiocirugía SNC
8. RADIOTERAPIA . SE CONTINU
9. Reinicio ITK (suspendió)
1(9.1%)
1(9.1%)
2(18.2%)
1(9.1%)
1(9.1%)
1(9.1%)
1(9.1%)
2(18.2%)
1(9.1%)
 11 (25.0%) 33 (75.0%)
134 FECHAS IMAGENES REVALORACION [Date]
min : 2016-10-01
med : 2023-11-21
max : 2025-05-08
range : 8y 7m 7d
 41 distinct values 43 (97.7%) 1 (2.3%)
135 FECHA DE RECAIDA [Date]
min : 2016-10-01
med : 2023-08-10
max : 2025-04-28
range : 8y 6m 27d
 11 distinct values 11 (25.0%) 33 (75.0%)
136 PROGRESIÓN O RECAIDA 1- MENOR AL AÑO 2- MAYOR AL AÑO [numeric]
Min : 1
Mean : 1.7
Max : 2
1:3(27.3%)
2:8(72.7%)
 11 (25.0%) 33 (75.0%)
137 MUERTE 1- MENOR AL AÑO 2- MAYOR AL AÑO [numeric]
Min : 1
Mean : 1.9
Max : 2
1:1(10.0%)
2:9(90.0%)
 10 (22.7%) 34 (77.3%)
138 ESTADO VITAL 1: VIVO 2: MUERTO [numeric]
Min : 1
Mean : 1.2
Max : 2
1:35(79.5%)
2:9(20.5%)
 44 (100.0%) 0 (0.0%)
139 ESTADO DE TRATAMIENTO [character]
1. ACTIVO
2. NO INICIÓ
3. SUSPENDIDO
32(72.7%)
1(2.3%)
11(25.0%)
 44 (100.0%) 0 (0.0%)
140 ÚLTIMO CONTROL [POSIXct, POSIXt]
min : 2024-01-05
med : 2025-04-07
max : 2025-05-17
range : 1y 4m 12d
 37 distinct values 44 (100.0%) 0 (0.0%)
141 fecha biopsia [Date]
min : 2006-01-01
med : 2023-02-14
max : 2024-11-29
range : 18y 10m 28d
 42 distinct values 43 (97.7%) 1 (2.3%)
142 fecha inicio itK [Date]
min : 2019-03-26
med : 2023-07-29
max : 2025-01-09
range : 5y 9m 14d
 40 distinct values 43 (97.7%) 1 (2.3%)
143 Dias a inicio de iTK desde dx histopatologico [numeric]
Mean (sd) : 220.8 (814.7)
min ≤ med ≤ max:
6 ≤ 82 ≤ 5418
IQR (CV) : 88.5 (3.7)
 41 distinct values 43 (97.7%) 1 (2.3%)
144 Concordante con guia 0=no 1=si [numeric]
Min : 0
Mean : 1
Max : 1
0:2(4.5%)
1:42(95.5%)
 44 (100.0%) 0 (0.0%)
145 Adherencia 0=no 1=si (asumir que si a menos que en HC diga que problemas para entrega) [numeric]
Min : 0
Mean : 0.9
Max : 1
0:3(6.8%)
1:41(93.2%)
 44 (100.0%) 0 (0.0%)

Generated by summarytools 1.1.4 (R version 4.4.2)
2025-09-14

Revision presencia evento - cuadro de seguimiento

library(dplyr)
library(lubridate)
library(knitr)
library(kableExtra)

# 1. Convertir las fechas a clase Date
BASE <- BASE %>%
  mutate(
    INICIO = as.Date(BASE$`FECHA DE DIAGNOSTICO (FECHA DE BIOPSIA)`, format = "%d/%m/%Y"),
    MUERTE = as.Date(BASE$`FECHA DE MUERTE`, format = "%d/%m/%Y"),
    PROGRE = as.Date(BASE$`FECHA DE PROGRESIÓN`, format = "%d/%m/%Y"),
    RECAIDA = as.Date(BASE$`FECHA DE RECAIDA`, format = "%d/%m/%Y"),
    SEGUIM = as.Date(BASE$`ÚLTIMO CONTROL`, format = "%d/%m/%Y")
  )


# 2. Definir fecha del evento (muerte o progresión) o censura
BASE <- BASE %>%
  mutate(
    fecha_evento = coalesce(MUERTE, PROGRE, SEGUIM),   # toma la primera no-NA
    Tiempo_meses = interval(INICIO, fecha_evento) %/% months(1),
    evento = ifelse(!is.na(MUERTE) | !is.na(PROGRE), 1, 0),  # 1 = evento, 0 = censura
    ID = row_number()
  )

# 3. Seleccionar las variables clave
SUP <- BASE %>% select(ID, Tiempo_meses, evento)

# 4. Visualizar en tabla bonita
kable(SUP, format = "html", table.attr = "style='width:60%;'") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))
ID Tiempo_meses evento
1 61 1
2 21 1
3 58 0
4 25 1
5 46 0
6 38 0
7 36 0
8 26 1
9 30 0
10 32 0
11 14 1
12 28 0
13 29 0
14 28 0
15 14 1
16 21 0
17 15 0
18 18 0
19 18 0
20 16 0
21 10 0
22 6 0
23 5 0
24 8 0
25 25 1
26 5 1
27 55 1
28 222 1
29 30 1
30 35 0
31 21 0
32 17 1
33 17 0
34 15 0
35 17 0
36 22 1
37 14 0
38 23 1
39 14 0
40 5 0
41 12 1
42 57 1
43 36 0
44 48 1

Identificando las censuras

library(survival)
Surv(SUP$Tiempo_meses, SUP$evento)
##  [1]  61   21   58+  25   46+  38+  36+  26   30+  32+  14   28+  29+  28+  14 
## [16]  21+  15+  18+  18+  16+  10+   6+   5+   8+  25    5   55  222   30   35+
## [31]  21+  17   17+  15+  17+  22   14+  23   14+   5+  12   57   36+  48

Graficando el seguimiento

library(ggplot2)
library(plotly)
SUP$evento2 <- factor(SUP$evento, levels = c(0,1), labels = c("Censura", "Evento"))
m <- SUP %>%
  mutate(t_inicio = 0,
         t_fin = Tiempo_meses) %>%
  ggplot(aes(x = as.factor(ID), y = t_fin)) +
  geom_linerange(aes(ymin = t_inicio, ymax = t_fin)) +
  geom_point(aes(shape = factor(evento2), color = factor(evento2)), stroke = 1, size = 2) +
  scale_shape_manual(values = c(1, 4)) +  # Diferentes formas para censura y eventos
  labs(y = "Tiempo de Supervivencia (meses)", x = "ID") + 
  coord_flip() + 
  theme_classic() +
  theme(legend.title = element_blank(), legend.position = "bottom")
ggplotly(m)

Limpieza de la base de datos


library(dplyr)

#ESTRATO
BASE <- BASE %>% 
  mutate(
    Estrato_cat = cut(
      ESTRATO, 
      breaks = c(-Inf, 2, 3, Inf), 
      right = TRUE,
      labels = c("1-2", "3", "4-5")
    )
  )

#EDAD
BASE$EDAD <- round(as.numeric(BASE$`FECHA DE DIAGNOSTICO (FECHA DE BIOPSIA)`- BASE$`FECHA NACIMIENTO`) / 365, 2)

#ESTADIO
BASE$ESTADIO_CAT <- ifelse(BASE$ESTADIO %in% c("IA3", "IB"), "IA3 - IB", ifelse(BASE$ESTADIO %in% c("IIIa", "IIIA", "IIIB"), "IIIA - IIIB", ifelse(BASE$ESTADIO %in% c("IV","IVa","IVA",  "IVB"), "IV - IVA - IVB", BASE$ESTADIO)))

#PERFIL MUTACIONAL
BASE$`PERFIL MUTACIONAL` <- tolower(BASE$`PERFIL MUTACIONAL`)
library(stringi)
BASE$`PERFIL MUTACIONAL` <- stri_trans_general(BASE$`PERFIL MUTACIONAL`, "Latin-ASCII")
BASE$`PERFIL MUTACIONAL`[BASE$`PERFIL MUTACIONAL` == "egfr delecion de exon 19"] <- "egfr del exon 19"
BASE$`PERFIL MUTACIONAL`[BASE$`PERFIL MUTACIONAL` == "egfr exon 20 l858r exon 21"] <- "egfr exon 21"

#PDL-1
BASE$`PDL-1` <- ifelse(BASE$`PDL-1` %in% c("0", "< 1", "<1"), "<1", ifelse(BASE$`PDL-1` %in% c("1", "5"), "1-5", ifelse(BASE$`PDL-1` %in% c("10"), "6-10", ifelse(BASE$`PDL-1` %in% c(">10", "95"), ">10",BASE$`PDL-1`))))

BASE$`PDL-1`<- factor(BASE$`PDL-1`, levels = c("<1", "1-5", "6-10", ">10") )

#Estimar diferencias 1 momento 

BASE$dif_Trat_ingreso <- round(as.numeric(BASE$`FECHA DE INICIO DE TRATAMIENTO CX-QXT-RXT-INMUNO`- BASE$`FECHA DE INGRESO`) / 30, 2)

ver_dif_Trat_ingreso  <- BASE[BASE$dif_Trat_ingreso < 0, ]
#ver_dif_Trat_ingreso$ID, se deben arreglar los ID: 5,9,16,28,29,36,38,39,40,41,42,44


#Tener o no cuidado paliativo 
BASE$Cuidado_Palativo <- factor(ifelse(!is.na(BASE[,92]), "Si", "No"))



#Modalidad de tratamiento
BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` <- tolower(BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO`)
BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` <- gsub("[\r\n]", " ", BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO`)
BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` <- trimws(BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO`)  # quitar espacios extra al inicio/fin

BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` <- ifelse(BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` %in% c("quimioterapia", "quimiterapia"), "quimioterapia", ifelse(BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO` %in% c("quimioterapia    itk", "terapia dirigida - quimioterapia"), "quimioterapia itk",  BASE$`MODALIDAD DE TRATAMIENTO ORDE.DO`))


BASE <- BASE %>%
  mutate(
    Modalidad_trat_recoded = case_when(
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "cirugia" ~ "Cirugía",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "itk" ~ "ITK",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "paliativo" ~ "Paliativo",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "quimioterapia" ~ "QT",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "quimioterapia itk" ~ "QT + ITK",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "qumioterapia" ~ "QT*", # Esta parece ser un error tipográfico
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "radioterapia" ~ "RT",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "radioterapia- quimioterapia - terapia dirigida" ~ "RT + QT + TD",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "radioterapia - quimioterapia" ~ "RT + QT",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "radioterapia - terapia dirigida" ~ "RT + TD",
      `MODALIDAD DE TRATAMIENTO ORDE.DO` == "terapia dirigida" ~ "TD",
      TRUE ~ as.character(`MODALIDAD DE TRATAMIENTO ORDE.DO`)  # Para cualquier otro caso
    )
  )


#Se elimina el dato problematico
BASE_L <- BASE[c(-28),]

#Se hace un grafico de seguimiento

SUP2 <- BASE_L %>% select(ID, Tiempo_meses, evento, SEXO, ESTADIO_CAT,Estrato_cat,Cuidado_Palativo, Charlson, `PERFIL MUTACIONAL`, `PDL-1`, Modalidad_trat_recoded)

SUP2$Evento <- factor(SUP2$evento, levels = c(0,1), labels = c("Censura", "Evento"))
m2 <- SUP2 %>%
  mutate(t_inicio = 0,
         t_fin = Tiempo_meses) %>%
  ggplot(aes(x = as.factor(ID), y = t_fin)) +
  geom_linerange(aes(ymin = t_inicio, ymax = t_fin)) +
  geom_point(aes(shape = factor(Evento), color = factor(Evento)), stroke = 1, size = 2) +
  scale_shape_manual(values = c(1, 4)) +  # Diferentes formas para censura y eventos
  labs(y = "Tiempo de Supervivencia (meses)", x = "ID") + 
  coord_flip() + 
  theme_classic() +
  theme(legend.title = element_blank(), legend.position = "bottom")
ggplotly(m2)

Se corre nuevamente el analisis descriptivo - exploratorio


print(dfSummary(BASE_L), method = "render")

Data Frame Summary

BASE_L

Dimensions: 43 x 162
Duplicates: 0
No Variable Stats / Values Freqs (% of Valid) Graph Valid Missing
1 ID [integer]
Mean (sd) : 22.4 (13)
min ≤ med ≤ max:
1 ≤ 22 ≤ 44
IQR (CV) : 22 (0.6)
 43 distinct values 43 (100.0%) 0 (0.0%)
2 NOMBRE DE PACIENTE [character]
1. A. ISABEL SANCHEZ MANZANE
2. ALEYDA YALILE BEJARANO JA
3. ALVARO SILVA ROZO
4. ANA GILMA TENJO AVIRAMA
5. BEATRIZ LOPEZ DE BONILLA
6. BLANCA CECILIA HERNANDEZ
7. BLANCA INES RAMOS SOSA
8. BLANCA INES SANCHEZ ALVAR
9. CARMEN ESTHER REDONDO ORT
10. CONSUELO CASTILLO RESTREP
[ 33 others ]
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
33(76.7%)
 43 (100.0%) 0 (0.0%)
3 DOCUMENTO [numeric]
Mean (sd) : 58263094 (159032073)
min ≤ med ≤ max:
2515356 ≤ 39565808 ≤ 1072660632
IQR (CV) : 20835579 (2.7)
 43 distinct values 43 (100.0%) 0 (0.0%)
4 EPS [character]
1. ALIANSALUD
2. CAFAM
3. COLMEDICA
4. COMPENSAR
5. NUEVA EPS
10(23.3%)
2(4.7%)
1(2.3%)
26(60.5%)
4(9.3%)
 43 (100.0%) 0 (0.0%)
5 ESTRATO [numeric]
Mean (sd) : 2.7 (1)
min ≤ med ≤ max:
1 ≤ 3 ≤ 5
IQR (CV) : 1 (0.4)
1:6(16.7%)
2:5(13.9%)
3:20(55.6%)
4:3(8.3%)
5:2(5.6%)
 36 (83.7%) 7 (16.3%)
6 SEXO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:35(81.4%)
1:8(18.6%)
 43 (100.0%) 0 (0.0%)
7 FECHA NACIMIENTO [Date]
min : 1939-11-11
med : 1953-01-02
max : 1991-05-14
range : 51y 6m 3d
 43 distinct values 43 (100.0%) 0 (0.0%)
8 TALLA (M) [numeric]
Mean (sd) : 1.6 (0.1)
min ≤ med ≤ max:
1.4 ≤ 1.6 ≤ 1.8
IQR (CV) : 0.1 (0.1)
 26 distinct values 43 (100.0%) 0 (0.0%)
9 PESO (KG) [numeric]
Mean (sd) : 59.8 (11.5)
min ≤ med ≤ max:
37 ≤ 62 ≤ 86
IQR (CV) : 13.5 (0.2)
 27 distinct values 43 (100.0%) 0 (0.0%)
10 IMC [numeric]
Mean (sd) : 24.2 (4.4)
min ≤ med ≤ max:
15.8 ≤ 23.9 ≤ 38.2
IQR (CV) : 5.1 (0.2)
 43 distinct values 43 (100.0%) 0 (0.0%)
11 GLAUCOMA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
12 HPB [numeric]
Min : 0
Mean : 0
Max : 1
0:41(95.3%)
1:2(4.7%)
 43 (100.0%) 0 (0.0%)
13 TUBERCULOSIS [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
14 LES [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
15 DESPRENDIMIENTO RETI. [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
16 ESTEATOSIS [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
17 VALVULOPATIA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
18 MENINGIOMA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
19 VASCULITIS [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
20 ACV [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
21 ADENOMA HIPOFISIARIO [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
22 MIOMATOSIS UTERINA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
23 ENFERMEDAD DIVERTICULAR [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
24 COLON IRRITABLE [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
25 CARDIOPATÍA HIPERTENSIVA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
26 DEPRESIÓN [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
27 CEFALEA PRIMARIA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
28 EPILEPSIA [numeric]
Min : 0
Mean : 0
Max : 1
0:41(95.3%)
1:2(4.7%)
 43 (100.0%) 0 (0.0%)
29 HIPOTIROIDISMO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:33(76.7%)
1:10(23.3%)
 43 (100.0%) 0 (0.0%)
30 HT PULMONAR [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
31 SD GILBERT [numeric]
Min : 0
Mean : 0.1
Max : 1
0:40(93.0%)
1:3(7.0%)
 43 (100.0%) 0 (0.0%)
32 SAHOS [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(90.7%)
1:4(9.3%)
 43 (100.0%) 0 (0.0%)
33 EPOC [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
34 CARDIOPATÍA ISQUÉMICA [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
35 ARRITMIAS [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
36 ETEV [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(90.7%)
1:4(9.3%)
 43 (100.0%) 0 (0.0%)
37 VÉRTIGO [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
38 CONSUMO PSICOACTIVOS [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
39 TRASTORNO ADAPTATIVO [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
40 CAVERNOMATOSIS MÚLTIPLE [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
41 HIPERTENSIÓN [numeric]
Min : 0
Mean : 0.4
Max : 1
0:25(58.1%)
1:18(41.9%)
 43 (100.0%) 0 (0.0%)
42 DISLIPIDEMIA [numeric]
Min : 0
Mean : 0.1
Max : 1
0:39(90.7%)
1:4(9.3%)
 43 (100.0%) 0 (0.0%)
43 PREDIABETES [numeric]
Min : 0
Mean : 0
Max : 1
0:41(95.3%)
1:2(4.7%)
 43 (100.0%) 0 (0.0%)
44 DIABETES [numeric]
Min : 0
Mean : 0.1
Max : 1
0:37(86.0%)
1:6(14.0%)
 43 (100.0%) 0 (0.0%)
45 SOBREPESO [numeric]
Min : 0
Mean : 0
Max : 1
0:41(95.3%)
1:2(4.7%)
 43 (100.0%) 0 (0.0%)
46 OBESIDAD [numeric]
Min : 0
Mean : 0
Max : 1
0:41(95.3%)
1:2(4.7%)
 43 (100.0%) 0 (0.0%)
47 ARTROSIS [numeric]
Min : 0
Mean : 0.1
Max : 1
0:40(93.0%)
1:3(7.0%)
 43 (100.0%) 0 (0.0%)
48 OSTEOPOROSIS [numeric]
Min : 0
Mean : 0.1
Max : 1
0:37(86.0%)
1:6(14.0%)
 43 (100.0%) 0 (0.0%)
49 HIPERPLASIA ENDOMETRIAL [numeric]
Min : 0
Mean : 0
Max : 1
0:42(97.7%)
1:1(2.3%)
 43 (100.0%) 0 (0.0%)
50 Charlson [numeric]
Mean (sd) : 8.9 (1.8)
min ≤ med ≤ max:
5 ≤ 9 ≤ 15
IQR (CV) : 1.5 (0.2)
5:1(2.3%)
6:2(4.7%)
7:4(9.3%)
8:9(20.9%)
9:16(37.2%)
10:7(16.3%)
11:2(4.7%)
14:1(2.3%)
15:1(2.3%)
 43 (100.0%) 0 (0.0%)
51 Otra neoplasia concomitante [numeric]
Min : 0
Mean : 0.2
Max : 1
0:36(83.7%)
1:7(16.3%)
 43 (100.0%) 0 (0.0%)
52 SOLO SI NEOPLASIA [character]
1. Ca ca.l a.l - Ca endometr
2. Ca Cromófobo de riñón 201
3. Ca de mama ductal
4. Ca papilar tiroides, CBC
5. Ca seroso de endometrio
6. Leucemia linfocítica crón
7. Linfoma cutáneo
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
1(14.3%)
 7 (16.3%) 36 (83.7%)
53 ANTECEDENTE TABAQUISMO [numeric]
Min : 0
Mean : 0.3
Max : 1
0:31(72.1%)
1:12(27.9%)
 43 (100.0%) 0 (0.0%)
54 ANTECEDENTE FAMILIAR DE CANCER [numeric]
Min : 0
Mean : 0.3
Max : 1
0:28(65.1%)
1:15(34.9%)
 43 (100.0%) 0 (0.0%)
55 ECOG [numeric]
Mean (sd) : 1.1 (0.8)
min ≤ med ≤ max:
0 ≤ 1 ≤ 3
IQR (CV) : 0 (0.7)
0:9(20.9%)
1:25(58.1%)
2:6(14.0%)
3:3(7.0%)
 43 (100.0%) 0 (0.0%)
56 KARNOSFKY [numeric]
Mean (sd) : 84.7 (15.8)
min ≤ med ≤ max:
40 ≤ 90 ≤ 100
IQR (CV) : 0 (0.2)
40:1(2.3%)
50:3(7.0%)
60:3(7.0%)
70:2(4.7%)
80:1(2.3%)
90:25(58.1%)
100:8(18.6%)
 43 (100.0%) 0 (0.0%)
57 VALORACION GERIATRICA INTEGRAL [numeric]
Min : 0
Mean : 0.1
Max : 1
0:38(88.4%)
1:5(11.6%)
 43 (100.0%) 0 (0.0%)
58 DIAGNOSTICO [numeric]
Mean (sd) : 1.2 (0.6)
min ≤ med ≤ max:
1 ≤ 1 ≤ 3
IQR (CV) : 0 (0.5)
1:37(86.0%)
2:3(7.0%)
3:3(7.0%)
 43 (100.0%) 0 (0.0%)
59 ESTADIO [character]
1. IA3
2. IB
3. IIA
4. IIIa
5. IIIA
6. IIIB
7. IV
8. IVa
9. IVA
10. IVB
1(2.3%)
2(4.7%)
2(4.7%)
1(2.3%)
1(2.3%)
2(4.7%)
28(65.1%)
2(4.7%)
2(4.7%)
2(4.7%)
 43 (100.0%) 0 (0.0%)
60 T [character]
1. 1
2. 1c
3. 1C
4. 2
5. 2A
6. 2B
7. 3
8. 3A
9. 4
10. x
11. X
1(2.3%)
1(2.3%)
1(2.3%)
7(16.3%)
2(4.7%)
3(7.0%)
6(14.0%)
1(2.3%)
11(25.6%)
1(2.3%)
9(20.9%)
 43 (100.0%) 0 (0.0%)
61 N [character]
1. 0
2. 1
3. 2
4. 2A
5. 3
6. X
7(16.3%)
4(9.3%)
6(14.0%)
1(2.3%)
9(20.9%)
16(37.2%)
 43 (100.0%) 0 (0.0%)
62 M [character]
1. 0
2. 1
3. 1C
10(23.3%)
32(74.4%)
1(2.3%)
 43 (100.0%) 0 (0.0%)
63 PLEURA [numeric]
Min : 0
Mean : 0.2
Max : 1
0:33(76.7%)
1:10(23.3%)
 43 (100.0%) 0 (0.0%)
64 MET HEPATICA [numeric]
Min : 0
Mean : 0.1
Max : 1
0:38(88.4%)
1:5(11.6%)
 43 (100.0%) 0 (0.0%)
65 MET GANGLIONAR [numeric]
Min : 0
Mean : 0.1
Max : 1
0:38(88.4%)
1:5(11.6%)
 43 (100.0%) 0 (0.0%)
66 MET SNC [numeric]
Min : 0
Mean : 0.2
Max : 1
0:33(76.7%)
1:10(23.3%)
 43 (100.0%) 0 (0.0%)
67 METS HUESO [numeric]
Min : 0
Mean : 0.3
Max : 1
0:28(65.1%)
1:15(34.9%)
 43 (100.0%) 0 (0.0%)
68 MET PULMON CONTRALATERAL [numeric]
Min : 0
Mean : 0.4
Max : 1
0:26(60.5%)
1:17(39.5%)
 43 (100.0%) 0 (0.0%)
69 TRATAMIENTO DE METASTASIS 0=Cirugía, 1=Radioterapia, 2= Ninguno [character]
1. .
2. 0
3. 1
4. 2
6(14.0%)
2(4.7%)
14(32.6%)
21(48.8%)
 43 (100.0%) 0 (0.0%)
70 DIAGNÓSTICO HISTOLÓGICO [numeric] 1 distinct value
2:43(100.0%)
 43 (100.0%) 0 (0.0%)
71 GRADO DE DIFERENCIACIÓN [numeric]
Mean (sd) : 2.3 (0.6)
min ≤ med ≤ max:
1 ≤ 2 ≤ 3
IQR (CV) : 1 (0.3)
1:2(6.9%)
2:16(55.2%)
3:11(37.9%)
 29 (67.4%) 14 (32.6%)
72 VARIANTE HISTOPATOLÓGICA [character]
1. Adenoescamoso
2. NSCLC
3. NSCLC (transformación a S
2(4.7%)
40(93.0%)
1(2.3%)
 43 (100.0%) 0 (0.0%)
73 VARIANTES DE ADENOCARCINOMA [character]
1. Variante Aci.r
2. Aci.r
3. Adenoescamoso
4. Aci.r 40% papilar 30% lep
5. Aci.r mucinoso
6. adenocarcinoma metastasic
7. Carcinoma de celula grand
8. Carcinoma de patrón lepíd
9. Célula grande
10. Celula no pequeña
[ 7 others ]
7(28.0%)
2(8.0%)
2(8.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
1(4.0%)
7(28.0%)
 25 (58.1%) 18 (41.9%)
74 PERFIL MUTACIONAL [character]
1. egfr del exon 19
2. egfr exon 21
30(69.8%)
13(30.2%)
 43 (100.0%) 0 (0.0%)
75 PDL-1 [factor]
1. <1
2. 1-5
3. 6-10
4. >10
26(76.5%)
4(11.8%)
2(5.9%)
2(5.9%)
 34 (79.1%) 9 (20.9%)
76 TMB (mut/megaPb) [numeric]
Min : 0.6
Mean : 14.4
Max : 28.2
 2 distinct values 2 (4.7%) 41 (95.3%)
77 MEDIASTINOSCOPIA DX PREVIA A CIRUGIA: 1.SI 0.NO [numeric]
Mean (sd) : 0.3 (0.6)
min ≤ med ≤ max:
0 ≤ 0 ≤ 2
IQR (CV) : 0 (2)
0:20(76.9%)
1:4(15.4%)
2:2(7.7%)
 26 (60.5%) 17 (39.5%)
78 TIPO DE BIOPSIA [character]
1. BIOPSIA DE PULMON
2. BIOPSIA PLEURAL
3. BX PERCUTANEA
4. EBUS
5. EXCISIO.L
6. LOBECTOMIA
7. PLEURA PARIETAL
8. PULMO.R
9. PULMÓN PERCUTÁNEA
10. PULMÓN TRANSBRONQUIAL
1(3.2%)
6(19.4%)
1(3.2%)
1(3.2%)
5(16.1%)
1(3.2%)
1(3.2%)
1(3.2%)
12(38.7%)
2(6.5%)
 31 (72.1%) 12 (27.9%)
79 BIOPSIA POR TAC 1: SI 0: NO [numeric]
Min : 0
Mean : 0.6
Max : 1
0:11(40.7%)
1:16(59.3%)
 27 (62.8%) 16 (37.2%)
80 Broncoscopia 1, SI 0, NO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:22(75.9%)
1:7(24.1%)
 29 (67.4%) 14 (32.6%)
81 EBUS-EUS DIAGNÓSTICO ENFERMEDAD MEDIASTI.L PREVIO A CIRUGÍA: 1:SI 0:NO [numeric]
Min : 0
Mean : 0.2
Max : 1
0:29(82.9%)
1:6(17.1%)
 35 (81.4%) 8 (18.6%)
82 FECHA DE DIAGNOSTICO (FECHA DE BIOPSIA) [Date]
min : 2018-12-28
med : 2023-01-03
max : 2024-11-29
range : 5y 11m 1d
 41 distinct values 43 (100.0%) 0 (0.0%)
83 INGRESA A LA UFC DE PULMÓN [numeric]
Min : 0
Mean : 1
Max : 1
0:1(2.3%)
1:42(97.7%)
 43 (100.0%) 0 (0.0%)
84 FECHA DE INGRESO [Date]
min : 2019-03-11
med : 2023-07-21
max : 2025-02-10
range : 5y 10m 30d
 42 distinct values 42 (97.7%) 1 (2.3%)
85 FECHA DE 1ª VALORACION HUSI [Date]
min : 2019-02-15
med : 2023-03-28
max : 2024-12-23
range : 5y 10m 8d
 42 distinct values 43 (100.0%) 0 (0.0%)
86 ESPECIALIDAD DE INGRESO [character]
1. CIRUGIA DE TORAX
2. CUIDADOS PALIATIVOS
3. NEUMOLOGIA
4. ONCOLOGIA CLINICA
5. ONCOLOGIA CLINICA
5(11.6%)
1(2.3%)
3(7.0%)
1(2.3%)
33(76.7%)
 43 (100.0%) 0 (0.0%)
87 VIA DE INGRESO 1: AMBULATORIO 2: HOSPITALIZADO [numeric]
Min : 1
Mean : 1
Max : 2
1:41(95.3%)
2:2(4.7%)
 43 (100.0%) 0 (0.0%)
88 FECHA VALORACIÓN ONCOLOGÍA [Date] 1. 2023-11-08
1(100.0%)
 1 (2.3%) 42 (97.7%)
89 FECHA DE ORDEN JUNTA MEDICA [Date] 1. 2023-08-25
1(100.0%)
 1 (2.3%) 42 (97.7%)
90 FECHA PACIENTE COMPLETA ESTUDIOS POR EPS / IPS [Date]
min : 2019-03-07
med : 2023-06-10
max : 2025-01-16
range : 5y 10m 9d
 40 distinct values 41 (95.3%) 2 (4.7%)
91 FECHA DE JUNTA MEDICA [Date]
min : 2019-03-11
med : 2023-05-22
max : 2025-02-10
range : 5y 10m 30d
 40 distinct values 42 (97.7%) 1 (2.3%)
92 VALORACIÓN POR GRUPO DE SOPORTE CUIDADO PALIATIVO [POSIXct, POSIXt]
min : 2019-03-05
med : 2023-08-02
max : 2025-02-25
range : 5y 11m 20d
 39 distinct values 39 (90.7%) 4 (9.3%)
93 INDICACIÓN QUIRÚRGICA INICIAL [character]
1. CURATIVA
2. DIAGNÓSTICA
3. MEDIASTINOSCOPIA
4. NO APLICA
5. PALIATIVA
6. PELURECTOMIA PARIETAL
7. TERAPÉUTICA
1(5.6%)
6(33.3%)
1(5.6%)
6(33.3%)
1(5.6%)
1(5.6%)
2(11.1%)
 18 (41.9%) 25 (58.1%)
94 PROCEDIMIENTO QUIRÚRGICO [character]
1. 1. NINGU.
2. 11.RESECCIÓN TUMOR DEL ME
3. CUÑA
4. LOBECTOMIA
5. LOBECTOMÍA + VG
6. MEDIASTINOSCOPIA + VG
7. PLEURECTOMIA PARITETAL
8. PLEURECTOMIA POR TORACOSC
7(36.8%)
1(5.3%)
1(5.3%)
4(21.1%)
1(5.3%)
3(15.8%)
1(5.3%)
1(5.3%)
 19 (44.2%) 24 (55.8%)
95 BORDES COMPROMETIDOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [character]
1. LIBRES
2. NO
3. SI
4(57.1%)
2(28.6%)
1(14.3%)
 7 (16.3%) 36 (83.7%)
96 GANGLIOS RESECADOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [character]
1. 10
2. 13
3. 16
4. 7
5. 8
6. VACIAMIENTO N1 Y N2
1(12.5%)
1(12.5%)
2(25.0%)
1(12.5%)
2(25.0%)
1(12.5%)
 8 (18.6%) 35 (81.4%)
97 GANGLIOS COMPROMETIDOS - SOLO LLE.R SI CIRUGIA DE PRIMARIO [numeric]
Min : 0
Mean : 1.2
Max : 5
0:6(75.0%)
5:2(25.0%)
 8 (18.6%) 35 (81.4%)
98 FECHA DE ORDEN DE CIRUGÍA [Date] 1. 2023-06-06
1(100.0%)
 1 (2.3%) 42 (97.7%)
99 FECHA VALORACIÓN DE ANESTESIA [Date]
1. 1970-01-01
2. 2092-03-02
3. 2092-05-21
4. 2092-09-23
5. 2093-04-28
6. 2093-05-03
7. 2093-09-15
8. 2093-12-28
15(68.2%)
1(4.5%)
1(4.5%)
1(4.5%)
1(4.5%)
1(4.5%)
1(4.5%)
1(4.5%)
 22 (51.2%) 21 (48.8%)
100 FECHA DE CIRUGIA [Date]
min : 1970-01-01
med : 1970-01-01
max : 2094-01-19
range : 124y 0m 18d
 12 distinct values 26 (60.5%) 17 (39.5%)
101 MODALIDAD DE TRATAMIENTO ORDE.DO [character]
1. cirugia
2. itk
3. paliativo
4. quimioterapia
5. quimioterapia itk
6. qumioterapia
7. radioterapia
8. radioterapia- quimioterap
9. radioterapia - quimiotera
10. radioterapia - terapia di
11. terapia dirigida
2(4.7%)
7(16.3%)
1(2.3%)
6(14.0%)
6(14.0%)
3(7.0%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
14(32.6%)
 43 (100.0%) 0 (0.0%)
102 ESQUEMA DE QUIMIOTERAPIA [character]
1. CARBOPLATINO PEMETREXED
2. CISPLATINO PEMETREXED
3. NO APLICA
4. PENDIENTE
15(34.9%)
3(7.0%)
24(55.8%)
1(2.3%)
 43 (100.0%) 0 (0.0%)
103 FECHA DE ORDEN DE QUIMIOTERAPIA [Date]
All NA's
 0 (0.0%) 43 (100.0%)
104 FECHA INICIO QUIMIOTERAPIA [Date]
min : 1970-01-01
med : 2091-03-04
max : 2095-02-01
range : 125y 1m 0d
 20 distinct values 33 (76.7%) 10 (23.3%)
105 iTK ORDENADO [character]
1. ERLOTINIB
2. OSIMERTINIB
1(2.3%)
42(97.7%)
 43 (100.0%) 0 (0.0%)
106 FECHA DE ORDEN DE iTK [Date] 1. 2023-10-03
1(100.0%)
 1 (2.3%) 42 (97.7%)
107 FECHA INICIO iTK [Date]
min : 2019-03-26
med : 2023-07-23
max : 2025-01-29
range : 5y 10m 3d
 40 distinct values 43 (100.0%) 0 (0.0%)
108 RADIOTERAPIA [character]
1. NO
2. SI
3(15.0%)
17(85.0%)
 20 (46.5%) 23 (53.5%)
109 DOSIS RT ADMINISTRADA [character]
1. 20
2. 2 Gy
3. 20 gy
4. 20 Gy
5. 2000/400 cGy
6. 25 Gy
7. 25 LUEGO 30 GY
8. 30
9. 3000
10. 3000 GY
[ 7 others ]
2(11.1%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
1(5.6%)
7(38.9%)
 18 (41.9%) 25 (58.1%)
110 TIPO DE RADIOTERAPIA [character]
1. 3DCRT
2. IMRT
3. IMRT/HOLOCRANEA.
4. NO APLICA
5. Radiocirugía - GammaKnife
6. RADIOCIRUGIA FOTONES
7. SBRT
1(5.6%)
6(33.3%)
1(5.6%)
2(11.1%)
1(5.6%)
1(5.6%)
6(33.3%)
 18 (41.9%) 25 (58.1%)
111 RADIOTERAPIA HUESO [numeric]
Min : 0
Mean : 0.4
Max : 1
0:14(56.0%)
1:11(44.0%)
 25 (58.1%) 18 (41.9%)
112 RADIOTERAPIA SNC [numeric]
Min : 0
Mean : 0.2
Max : 1
0:19(76.0%)
1:6(24.0%)
 25 (58.1%) 18 (41.9%)
113 RADIOTERAPIA PULMON [numeric]
Min : 0
Mean : 0.2
Max : 1
0:21(84.0%)
1:4(16.0%)
 25 (58.1%) 18 (41.9%)
114 FECHA DE VALORACIÓN DE RADIOTERAPIA [Date]
min : 1970-01-01
med : 2092-06-08
max : 2094-10-12
range : 124y 9m 11d
 16 distinct values 23 (53.5%) 20 (46.5%)
115 FECHA DE INICIO DE RADIOTERAPIA [Date]
All NA's
 0 (0.0%) 43 (100.0%)
116 INTENCIÓN INICIAL DE TRATAMIENTO [character]
1. CURATIVO
2. PALIATIVO
3(7.0%)
40(93.0%)
 43 (100.0%) 0 (0.0%)
117 TRATAMIENTO INICIAL ORDENADO [character]
1. iTK
2. QUIMIOTERAPIA
3. ITK
4. CIRUGIA
5. CIRUGÍA
6. RADIOTERAPIA MET + iTK
7. CIRUGÍA DE RESECCIÓN
8. PALIATIVO
9. QUIMIOTERAPIA + iTK
10. QUIMIOTERAPIA
iTK
[ 3 others ]
19(44.2%)
7(16.3%)
4(9.3%)
2(4.7%)
2(4.7%)
2(4.7%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
3(7.0%)
 43 (100.0%) 0 (0.0%)
118 TRATAMIENTO ACTUAL [character]
1. CARBO/PEMETREXED
2. FLAURA-2
3. OSIMERTINIB
4. OSIMERTINIB - PEMETREXED
5. OSIMERTINIB
+ PEMETRE
6. OSIMERTINIB
CIRUGIA
Q
1(2.3%)
2(4.7%)
37(86.0%)
1(2.3%)
1(2.3%)
1(2.3%)
 43 (100.0%) 0 (0.0%)
119 FECHA DE INICIO DE TRATAMIENTO CX-QXT-RXT-INMUNO [Date]
min : 2019-03-26
med : 2023-07-23
max : 2025-01-30
range : 5y 10m 4d
 43 distinct values 43 (100.0%) 0 (0.0%)
120 OPORTUNIDAD DE JUNTA MEDICA [numeric]
Mean (sd) : 24.6 (54.1)
min ≤ med ≤ max:
-262 ≤ 21.5 ≤ 132
IQR (CV) : 39.8 (2.2)
 33 distinct values 42 (97.7%) 1 (2.3%)
121 OPORTUNIDAD DE VALORACIÒN PREANESTESIA [numeric]
Mean (sd) : 1.8 (5.1)
min ≤ med ≤ max:
0 ≤ 0 ≤ 23
IQR (CV) : 0 (2.9)
0:35(85.4%)
1:1(2.4%)
9:2(4.9%)
15:1(2.4%)
16:1(2.4%)
23:1(2.4%)
 41 (95.3%) 2 (4.7%)
122 OPORTUNIDAD DE CIRUGÍA [numeric]
Mean (sd) : 4308.6 (13242.3)
min ≤ med ≤ max:
0 ≤ 0 ≤ 44552
IQR (CV) : 0 (3.1)
 11 distinct values 41 (95.3%) 2 (4.7%)
123 OPORTUNIDAD DE INICIO QXT [numeric]
Mean (sd) : 6.4 (8.1)
min ≤ med ≤ max:
0 ≤ 0 ≤ 29
IQR (CV) : 13 (1.3)
 13 distinct values 41 (95.3%) 2 (4.7%)
124 OPORTUNIDAD DE INICIO TRATAMIENTO DIRIGIDO [numeric]
Mean (sd) : 8.2 (40.2)
min ≤ med ≤ max:
-239 ≤ 13 ≤ 47
IQR (CV) : 12.5 (4.9)
 27 distinct values 42 (97.7%) 1 (2.3%)
125 OPORTUNIDAD DE INICIO RXT [numeric]
Mean (sd) : 1096.3 (6941.6)
min ≤ med ≤ max:
0 ≤ 0 ≤ 44460
IQR (CV) : 17 (6.3)
 16 distinct values 41 (95.3%) 2 (4.7%)
126 OPORTUNIDAD DE INICIO DE TRATAMIENTO DESDE EL DIAGNÓSTICO POR PATOLOGÍA [numeric]
Mean (sd) : 83.9 (95.3)
min ≤ med ≤ max:
-13 ≤ 70 ≤ 565
IQR (CV) : 52.5 (1.1)
 39 distinct values 43 (100.0%) 0 (0.0%)
127 OPORTUNIDAD DE INICIO DESDE LA PRIMERA ATENCIÓN DEL HUSI [numeric]
Mean (sd) : 58.8 (111.6)
min ≤ med ≤ max:
-351 ≤ 41.5 ≤ 542
IQR (CV) : 68.2 (1.9)
 38 distinct values 42 (97.7%) 1 (2.3%)
128 FECHA DE MUERTE [Date]
1. 2024-01-26
2. 2024-02-19
3. 2024-05-07
4. 2024-05-10
5. 2024-07-08
6. 2024-07-15
7. 2024-12-09
8. 2025-01-31
1(11.1%)
1(11.1%)
1(11.1%)
1(11.1%)
2(22.2%)
1(11.1%)
1(11.1%)
1(11.1%)
 9 (20.9%) 34 (79.1%)
129 CAUSAS DE EGRESO [character] 1. MUERTE
9(100.0%)
 9 (20.9%) 34 (79.1%)
130 # DE DÍAS PCTE VIVO DESDE LA PATOLOGÍA [numeric]
Mean (sd) : 811.2 (502.4)
min ≤ med ≤ max:
129 ≤ 662 ≤ 2256
IQR (CV) : 614 (0.6)
 43 distinct values 43 (100.0%) 0 (0.0%)
131 # DE DÍAS PACTE VIVO DESDE INICIO DE TRATAMIENTO [numeric]
Mean (sd) : 727.3 (507.4)
min ≤ med ≤ max:
102 ≤ 588 ≤ 2168
IQR (CV) : 520 (0.7)
 41 distinct values 43 (100.0%) 0 (0.0%)
132 EDAD EN AÑOS (FALLECE) [numeric]
Mean (sd) : 70.2 (10.1)
min ≤ med ≤ max:
49 ≤ 70 ≤ 85
IQR (CV) : 10.8 (0.1)
 11 distinct values 12 (27.9%) 31 (72.1%)
133 FECHA DE DIAGNÓSTICO POR PATOLOGÍA [Date]
min : 2018-12-28
med : 2023-02-14
max : 2024-11-29
range : 5y 11m 1d
 42 distinct values 43 (100.0%) 0 (0.0%)
134 FECHA DE PROGRESIÓN [Date]
min : 2022-03-01
med : 2024-02-02
max : 2025-01-28
range : 2y 10m 27d
 11 distinct values 11 (25.6%) 32 (74.4%)
135 TIPO DE PROGRESIÓN 0=OLIGOPROGRESIÓN, 1=PROGRESIÓN [numeric]
Min : 0
Mean : 0.7
Max : 1
0:3(30.0%)
1:7(70.0%)
 10 (23.3%) 33 (76.7%)
136 TRATAMIENTO POSTERIOR A PROGRESIÓN [character]
1. Carboplatino/Etoposido/Du
2. FLAURA-2
3. OSIMERTINIB
4. QT
5. QT+INMUNO
6. QUIMIOTERAPIA
7. Radiocirugía SNC
8. RADIOTERAPIA . SE CONTINU
9. Reinicio ITK (suspendió)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
2(20.0%)
1(10.0%)
 10 (23.3%) 33 (76.7%)
137 FECHAS IMAGENES REVALORACION [Date]
min : 2020-01-10
med : 2023-11-22
max : 2025-05-08
range : 5y 3m 28d
 40 distinct values 42 (97.7%) 1 (2.3%)
138 FECHA DE RECAIDA [Date]
1. 2020-01-10
2. 2022-03-01
3. 2022-09-22
4. 2023-04-28
5. 2023-08-10
6. 2023-09-22
7. 2023-11-21
8. 2023-12-07
9. 2024-04-24
10. 2025-04-28
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
 10 (23.3%) 33 (76.7%)
139 PROGRESIÓN O RECAIDA 1- MENOR AL AÑO 2- MAYOR AL AÑO [numeric]
Min : 1
Mean : 1.7
Max : 2
1:3(30.0%)
2:7(70.0%)
 10 (23.3%) 33 (76.7%)
140 MUERTE 1- MENOR AL AÑO 2- MAYOR AL AÑO [numeric]
Min : 1
Mean : 1.9
Max : 2
1:1(11.1%)
2:8(88.9%)
 9 (20.9%) 34 (79.1%)
141 ESTADO VITAL 1: VIVO 2: MUERTO [numeric]
Min : 1
Mean : 1.2
Max : 2
1:35(81.4%)
2:8(18.6%)
 43 (100.0%) 0 (0.0%)
142 ESTADO DE TRATAMIENTO [character]
1. ACTIVO
2. NO INICIÓ
3. SUSPENDIDO
32(74.4%)
1(2.3%)
10(23.3%)
 43 (100.0%) 0 (0.0%)
143 ÚLTIMO CONTROL [POSIXct, POSIXt]
min : 2024-01-05
med : 2025-04-10
max : 2025-05-17
range : 1y 4m 12d
 36 distinct values 43 (100.0%) 0 (0.0%)
144 fecha biopsia [Date]
min : 2018-12-28
med : 2023-03-07
max : 2024-11-29
range : 5y 11m 1d
 41 distinct values 42 (97.7%) 1 (2.3%)
145 fecha inicio itK [Date]
min : 2019-03-26
med : 2023-08-07
max : 2025-01-09
range : 5y 9m 14d
 39 distinct values 42 (97.7%) 1 (2.3%)
146 Dias a inicio de iTK desde dx histopatologico [numeric]
Mean (sd) : 97.1 (73.8)
min ≤ med ≤ max:
6 ≤ 80.5 ≤ 322
IQR (CV) : 89 (0.8)
 40 distinct values 42 (97.7%) 1 (2.3%)
147 Concordante con guia 0=no 1=si [numeric]
Min : 0
Mean : 1
Max : 1
0:2(4.7%)
1:41(95.3%)
 43 (100.0%) 0 (0.0%)
148 Adherencia 0=no 1=si (asumir que si a menos que en HC diga que problemas para entrega) [numeric]
Min : 0
Mean : 0.9
Max : 1
0:3(7.0%)
1:40(93.0%)
 43 (100.0%) 0 (0.0%)
149 INICIO [Date]
min : 2018-12-28
med : 2023-01-03
max : 2024-11-29
range : 5y 11m 1d
 41 distinct values 43 (100.0%) 0 (0.0%)
150 MUERTE [Date]
1. 2024-01-26
2. 2024-02-19
3. 2024-05-07
4. 2024-05-10
5. 2024-07-08
6. 2024-07-15
7. 2024-12-09
8. 2025-01-31
1(11.1%)
1(11.1%)
1(11.1%)
1(11.1%)
2(22.2%)
1(11.1%)
1(11.1%)
1(11.1%)
 9 (20.9%) 34 (79.1%)
151 PROGRE [Date]
min : 2022-03-01
med : 2024-02-02
max : 2025-01-28
range : 2y 10m 27d
 11 distinct values 11 (25.6%) 32 (74.4%)
152 RECAIDA [Date]
1. 2020-01-10
2. 2022-03-01
3. 2022-09-22
4. 2023-04-28
5. 2023-08-10
6. 2023-09-22
7. 2023-11-21
8. 2023-12-07
9. 2024-04-24
10. 2025-04-28
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
1(10.0%)
 10 (23.3%) 33 (76.7%)
153 SEGUIM [Date]
min : 2024-01-05
med : 2025-04-10
max : 2025-05-17
range : 1y 4m 12d
 36 distinct values 43 (100.0%) 0 (0.0%)
154 fecha_evento [Date]
min : 2022-03-01
med : 2025-03-17
max : 2025-05-17
range : 3y 2m 16d
 39 distinct values 43 (100.0%) 0 (0.0%)
155 Tiempo_meses [numeric]
Mean (sd) : 24.9 (14.9)
min ≤ med ≤ max:
5 ≤ 21 ≤ 61
IQR (CV) : 16.5 (0.6)
 28 distinct values 43 (100.0%) 0 (0.0%)
156 evento [numeric]
Min : 0
Mean : 0.4
Max : 1
0:27(62.8%)
1:16(37.2%)
 43 (100.0%) 0 (0.0%)
157 Estrato_cat [factor]
1. 1-2
2. 3
3. 4-5
11(30.6%)
20(55.6%)
5(13.9%)
 36 (83.7%) 7 (16.3%)
158 EDAD [numeric]
Mean (sd) : 67.2 (10.8)
min ≤ med ≤ max:
32.7 ≤ 69.9 ≤ 83.5
IQR (CV) : 14.2 (0.2)
 43 distinct values 43 (100.0%) 0 (0.0%)
159 ESTADIO_CAT [character]
1. IA3 - IB
2. IIA
3. IIIA - IIIB
4. IV - IVA - IVB
3(7.0%)
2(4.7%)
4(9.3%)
34(79.1%)
 43 (100.0%) 0 (0.0%)
160 dif_Trat_ingreso [numeric]
Mean (sd) : 0 (5.7)
min ≤ med ≤ max:
-24.6 ≤ 0.4 ≤ 18.3
IQR (CV) : 1.1 (4790.4)
 36 distinct values 42 (97.7%) 1 (2.3%)
161 Cuidado_Palativo [factor]
1. No
2. Si
4(9.3%)
39(90.7%)
 43 (100.0%) 0 (0.0%)
162 Modalidad_trat_recoded [character]
1. Cirugía
2. ITK
3. Paliativo
4. QT
5. QT + ITK
6. QT*
7. RT
8. RT + QT
9. RT + QT + TD
10. RT + TD
11. TD
2(4.7%)
7(16.3%)
1(2.3%)
6(14.0%)
6(14.0%)
3(7.0%)
1(2.3%)
1(2.3%)
1(2.3%)
1(2.3%)
14(32.6%)
 43 (100.0%) 0 (0.0%)

Generated by summarytools 1.1.4 (R version 4.4.2)
2025-09-14

#Estimacion mediana de superviviencia

library(survival)
library(survminer)
SUP2$Evento <- as.numeric(SUP2$Evento)
SUP2$Evento[SUP2$Evento != 1] <- 0   # asegura que solo hay 0/1

surv_object <- Surv(time = SUP2$Tiempo_meses, event = SUP2$Evento)
fit <- survfit(surv_object ~ 1, data = SUP2)
summary_fit <- summary(fit)
df_summary <- data.frame(
  time     = summary_fit$time,
  n.risk   = summary_fit$n.risk,
  n.event  = summary_fit$n.event,
  survival = summary_fit$surv,
  std.err  = summary_fit$std.err,
  upper    = summary_fit$upper,
  lower    = summary_fit$lower
)


kable(df_summary, format = "html", table.attr = "style='width:80%;'") %>%
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))
time n.risk n.event survival std.err upper lower
5 43 2 0.9534884 0.0321147 1.0000000 0.8925773
6 40 1 0.9296512 0.0391719 1.0000000 0.8559604
8 39 1 0.9058140 0.0448375 0.9980981 0.8220624
10 38 1 0.8819767 0.0495908 0.9847308 0.7899448
14 36 2 0.8329780 0.0576830 0.9540662 0.7272581
15 32 2 0.7809169 0.0647680 0.9187601 0.6637546
16 30 1 0.7548863 0.0676380 0.8998071 0.6333062
17 29 2 0.7028252 0.0723005 0.8598277 0.5744910
18 26 2 0.6487617 0.0761780 0.8166461 0.5153907
21 24 2 0.5946983 0.0788407 0.7711567 0.4586176
28 16 2 0.5203610 0.0847151 0.7159471 0.3782061
29 14 1 0.4831923 0.0864341 0.6860949 0.3402953
30 13 1 0.4460237 0.0874125 0.6549043 0.3037652
32 11 1 0.4054761 0.0883712 0.6215553 0.2645152
35 10 1 0.3649285 0.0883480 0.5865174 0.2270569
36 9 2 0.2838333 0.0853186 0.5115988 0.1574697
38 7 1 0.2432857 0.0822026 0.4717641 0.1254608
46 6 1 0.2027380 0.0778630 0.4303731 0.0955048
58 2 1 0.1013690 0.0815690 0.4907324 0.0209395

Curva de superviviencia

ggsurvplot(
  fit, 
  data = SUP2,
  conf.int = TRUE,                 # mostrar intervalo de confianza
  risk.table = TRUE,               # mostrar tabla de número en riesgo
  pval = TRUE,                     # valor p si hay grupos
  surv.median.line = "hv",         # línea en mediana de supervivencia
  xlab = "Tiempo (meses)", 
  ylab = "Probabilidad de supervivencia",
  palette = "Dark2",               # paleta de colores
  ggtheme = theme_minimal(base_size = 14)
)

#Buscando posibles diferencias por las medianas de variables categoricas

colnames(SUP2)[9] <- "PERFIL_MUTACIONAL"
colnames(SUP2)[10] <- "PDL_1"
colnames(SUP2)[11] <- "Modalidad_trat"
survdiff(Surv(Tiempo_meses, Evento) ~ SEXO, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ SEXO, data = SUP2)
## 
##         N Observed Expected (O-E)^2/E (O-E)^2/V
## SEXO=0 35       22    22.66     0.019     0.123
## SEXO=1  8        5     4.34     0.099     0.123
## 
##  Chisq= 0.1  on 1 degrees of freedom, p= 0.7
survdiff(Surv(Tiempo_meses, Evento) ~ ESTADIO_CAT, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ ESTADIO_CAT, 
##     data = SUP2)
## 
##                             N Observed Expected (O-E)^2/E (O-E)^2/V
## ESTADIO_CAT=IA3 - IB        3        2    2.560     0.123     0.147
## ESTADIO_CAT=IIA             2        2    0.765     1.996     2.165
## ESTADIO_CAT=IIIA - IIIB     4        3    1.407     1.803     1.987
## ESTADIO_CAT=IV - IVA - IVB 34       20   22.268     0.231     1.408
## 
##  Chisq= 4.4  on 3 degrees of freedom, p= 0.2
survdiff(Surv(Tiempo_meses, Evento) ~ Estrato_cat, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ Estrato_cat, 
##     data = SUP2)
## 
## n=36, 7 observations deleted due to missingness.
## 
##                  N Observed Expected (O-E)^2/E (O-E)^2/V
## Estrato_cat=1-2 11        6     6.45     0.031    0.0459
## Estrato_cat=3   20       13    11.36     0.236    0.5052
## Estrato_cat=4-5  5        3     4.19     0.339    0.4388
## 
##  Chisq= 0.6  on 2 degrees of freedom, p= 0.7
survdiff(Surv(Tiempo_meses, Evento) ~ Cuidado_Palativo, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ Cuidado_Palativo, 
##     data = SUP2)
## 
##                      N Observed Expected (O-E)^2/E (O-E)^2/V
## Cuidado_Palativo=No  4        3     2.84   0.00878    0.0104
## Cuidado_Palativo=Si 39       24    24.16   0.00103    0.0104
## 
##  Chisq= 0  on 1 degrees of freedom, p= 0.9
survdiff(Surv(Tiempo_meses, Evento) ~ Charlson, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ Charlson, data = SUP2)
## 
##              N Observed Expected (O-E)^2/E (O-E)^2/V
## Charlson=5   1        1    0.344    1.2523    1.3174
## Charlson=6   2        1    0.302    1.6084    1.7067
## Charlson=7   4        1    2.632    1.0117    1.1670
## Charlson=8   9        8    6.289    0.4657    0.6391
## Charlson=9  16        8   10.871    0.7583    1.3204
## Charlson=10  7        5    3.963    0.2716    0.3307
## Charlson=11  2        2    2.179    0.0147    0.0184
## Charlson=14  1        1    0.242    2.3819    2.4970
## Charlson=15  1        0    0.179    0.1790    0.1866
## 
##  Chisq= 8.4  on 8 degrees of freedom, p= 0.4
survdiff(Surv(Tiempo_meses, Evento) ~ PERFIL_MUTACIONAL, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ PERFIL_MUTACIONAL, 
##     data = SUP2)
## 
##                                     N Observed Expected (O-E)^2/E (O-E)^2/V
## PERFIL_MUTACIONAL=egfr del exon 19 30       19    18.61    0.0083    0.0284
## PERFIL_MUTACIONAL=egfr exon 21     13        8     8.39    0.0184    0.0284
## 
##  Chisq= 0  on 1 degrees of freedom, p= 0.9
survdiff(Surv(Tiempo_meses, Evento) ~ PDL_1, data = SUP2)
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ PDL_1, data = SUP2)
## 
## n=34, 9 observations deleted due to missingness.
## 
##             N Observed Expected (O-E)^2/E (O-E)^2/V
## PDL_1=<1   26       15    14.68   0.00698    0.0322
## PDL_1=1-5   4        3     1.25   2.44967    2.7893
## PDL_1=6-10  2        1     1.40   0.11398    0.1288
## PDL_1=>10   2        0     1.67   1.67058    1.9044
## 
##  Chisq= 4.5  on 3 degrees of freedom, p= 0.2
survdiff(Surv(Tiempo_meses, Evento) ~ Modalidad_trat, data = SUP2) #solo se encontro diferencia por modaldiad de tratamiento
## Call:
## survdiff(formula = Surv(Tiempo_meses, Evento) ~ Modalidad_trat, 
##     data = SUP2)
## 
##                              N Observed Expected (O-E)^2/E (O-E)^2/V
## Modalidad_trat=Cirugía       2        1   0.8795    0.0165    0.0179
## Modalidad_trat=ITK           7        4   8.3097    2.2352    3.8014
## Modalidad_trat=Paliativo     1        1   0.0715   12.0553   12.5444
## Modalidad_trat=QT            6        6   3.0648    2.8112    3.3103
## Modalidad_trat=QT + ITK      6        4   4.3580    0.0294    0.0371
## Modalidad_trat=QT*           3        2   0.1902   17.2233   18.6034
## Modalidad_trat=RT            1        1   0.6291    0.2187    0.2357
## Modalidad_trat=RT + QT       1        0   0.5041    0.5041    0.5358
## Modalidad_trat=RT + QT + TD  1        0   0.5041    0.5041    0.5358
## Modalidad_trat=RT + TD       1        0   1.5001    1.5001    1.6948
## Modalidad_trat=TD           14        8   6.9889    0.1463    0.2137
## 
##  Chisq= 41.6  on 10 degrees of freedom, p= 9e-06
fit1 <- survfit(Surv(Tiempo_meses, evento) ~ Modalidad_trat, data = SUP2, type = "kaplan-meier")
ggsurvplot(
  fit1, 
  data = SUP2,
  xlab = "Tiempo en meses", 
  ylab = "Probabilidad de Supervivencia",
  title = "Curvas Kaplan-Meier según tratamiento",
  conf.int = FALSE,        # intervalos de confianza
  pval = TRUE,             # valor p del log-rank
  risk.table = TRUE,       # tabla de riesgo
  risk.table.fontsize = 3, # tamaño fuente tabla
  ggtheme = theme_minimal(),
  tables.theme = theme(
    text = element_text(size = 5),
    axis.text = element_text(size = 5),
    strip.text = element_text(size = 14)
  )
)


plot1 <- ggsurvplot(
  fit1, 
  data = SUP2,
  xlab = "Tiempo en meses", 
  ylab = "Probabilidad de Supervivencia",
  title = "Curvas Kaplan-Meier según tratamiento",
  conf.int = FALSE,        
  pval = TRUE,             
  risk.table = TRUE,       
  
  palette = c("#1B4F72", "#2874A6", "#3498DB", "#5DADE2", "#85C1E9", 
               "#2C3E50", "#566573", "#7F8C8D", "#95A5A6", "#BDC3C7", "#34495E"),

  # Configuración de la tabla de riesgo
  risk.table.fontsize = 3.5,
  risk.table.height = 0.4,    # Mayor altura para mejor legibilidad
  risk.table.y.text = TRUE,   # Mostrar etiquetas en Y
  
  # Tema principal
  ggtheme = theme_minimal() +
    theme(
      plot.title = element_text(size = 14, hjust = 0.5, face = "bold"),
      axis.title = element_text(size = 12),
      axis.text = element_text(size = 10),
      legend.title = element_text(size = 11),
      legend.text = element_text(size = 9),
      panel.grid.minor = element_blank()
    ),
  
  # Tema para tablas con mejor contraste
  tables.theme = theme_cleantable() +
    theme(
      plot.title = element_text(size = 11, hjust = 0.5, face = "bold"),
      axis.text.y = element_text(size = 10, color = "black", face = "bold"),
      axis.text.x = element_text(size = 10, color = "black"),
      axis.title = element_text(size = 11, face = "bold"),
      strip.text = element_text(size = 10, color = "black", face = "bold"),
      plot.background = element_rect(fill = "white", color = NA),
      panel.background = element_rect(fill = "grey98", color = NA)
    ),
  
  # Configuraciones adicionales
  tables.col = "black",
  legend.title = "Modalidad de\nTratamiento"
)

print(plot1)

# OPCIÓN 1: Gráfico con colores suaves y tabla mejorada
plot2 <- ggsurvplot(
  fit1, 
  data = SUP2,
  xlab = "Tiempo en meses", 
  ylab = "Probabilidad de Supervivencia",
  title = "Curvas Kaplan-Meier según tratamiento",
  conf.int = FALSE,        
  pval = TRUE,             
  risk.table = FALSE,       

  # Tema principal
  ggtheme = theme_minimal() +
    theme(
      plot.title = element_text(size = 14, hjust = 0.5, face = "bold"),
      axis.title = element_text(size = 12),
      axis.text = element_text(size = 10),
      legend.title = element_text(size = 11),
      legend.text = element_text(size = 9),
      panel.grid.minor = element_blank()
    ),
  
  # Tema para tablas con mejor contraste
  tables.theme = theme_cleantable() +
    theme(
      plot.title = element_text(size = 11, hjust = 0.5, face = "bold"),
      axis.text.y = element_text(size = 10, color = "black", face = "bold"),
      axis.text.x = element_text(size = 10, color = "black"),
      axis.title = element_text(size = 11, face = "bold"),
      strip.text = element_text(size = 10, color = "black", face = "bold"),
      plot.background = element_rect(fill = "white", color = NA),
      panel.background = element_rect(fill = "grey98", color = NA)
    ),
  
  # Configuraciones adicionales
  tables.col = "black",
  legend.title = "Modalidad de\nTratamiento"
) 
plot2

Grafico Sankey


#se codificia las nuevas variables

#1 Completitud del tratamiento Quimio + Radio + Braqui
BASE2 <- BASE_L
BASE2$evento <- factor(BASE2$evento,
                       levels = c(1, 0),
                       labels = c("Evento", "Censura"))

BASE2$ITK <- factor(ifelse(!is.na(BASE2$`FECHA INICIO iTK`), "+ITK", "-ITK"))
BASE2$quimio <- factor(ifelse(!is.na(BASE2$`FECHA INICIO QUIMIOTERAPIA`), "+quim", "-quim"))
BASE2$EGFR_cat <- ifelse(grepl("19", BASE2$`PERFIL MUTACIONAL`, ignore.case = TRUE),
                        "Exon19",
                        "Exon21")

BASE_AL <- BASE2 %>% select(EGFR_cat,ITK, quimio, evento)
BASE_transformado <- BASE_AL %>% group_by(EGFR_cat,ITK, quimio, evento) %>% 
  summarise(Freq = n()) %>% ungroup() %>% rename(EGFR = EGFR_cat, ITK = ITK, quimio = quimio, evento = evento)


library(easyalluvial) 

alluvial_wide( data = BASE_AL, 
               max_variables = 4, fill_by = 'first_variable',
               col_vector_flow = c("skyblue", "salmon"))


kable(BASE_transformado)
EGFR ITK quimio evento Freq
Exon19 +ITK -quim Evento 2
Exon19 +ITK -quim Censura 5
Exon19 +ITK +quim Evento 9
Exon19 +ITK +quim Censura 14
Exon21 +ITK -quim Evento 1
Exon21 +ITK -quim Censura 2
Exon21 +ITK +quim Evento 4
Exon21 +ITK +quim Censura 6