SIMPULAN DAN SARAN
7.1 Simpulan
Setelah dilakukan penelitian tentang faktor-faktor yang berhubungan dengan
loss to follow up pada odha yang menerima terapi ARV di Klinik Amertha
Yayasan Kerti Praja Bali Tahun 2002-2012, dapat disimpulkan bahwa dari 10 variabel yang diteliti, tiga variabel yang terbukti secara statistik berhubungan dengan loss to follow up. Loss to follow up lebih besar pada odha yang tidak memiliki PMO, odha dengan umur ≤32 tahun, dan odha pada kelompok heteroseksual sebagai pekerja seksual. Sedangkan variabel jenis kelamin, tingkat pendidikan, jenis pekerjaan, kadar CD4, berat badan, hemoglobin, dan infeksi oportunisik tidak terbukti secara statistik memiliki hubungan terhadap loss to
follow up.
7.2 Saran
Untuk mengurangi loss to follow up pada odha yang menerima terapi ARV dapat disarankan kepada provider untuk melakukan pendampingan yang lebih intensif pada mereka, terutama untuk pekerja seks. Konseling yang lebih intensif juga perlu diberikan pada odha yang berumur lebih muda sebelum memulai terapi ARV. Selain itu diperlukan penelitian lain yang menggunakan data primer seperti penelitian kualitatif untuk dapat mengetahui alasan mengapa odha loss to follow
62
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Lampiran 1
FORMULIR PENGUMPULAN DATA PASIEN
HIV/AIDS YANG MELAKUKAN TERAPI ARV DI
KLINIK YAYASAN KERTI PRAJA BALI TAHUN
2002-2012
DATA DEMOGRAFI PASIEN
NO VARIABEL DATA 1 Nama Pasien2 No RM
3 Tanggal Lahir / Umur (saat kunjungan pertama) 4 Nama Konselor 5 Jenis Kelamin 6 Risiko atau Paparan
(saat kunjungan pertama)
1. Risiko seksual
(Jabarkan apa risikonya: misalnya apakah ganti-ganti pasangan, bagaimana pemakaian kondom, mencari pekerja seks, mencari waria, cewek café) 2. Risiko IDU
(Jabarkan apa risikonya: misalnya apakah
menggunakan jarum suntik, menyuntik bersama)
3. Risiko lainnya (jelaskan: misal tatto, piercing, transfuse darah)
7 Pekerjaan 8 Pendidikan
9 Kadar CD4 Tanggal Test CD4 Pertama Kali: Hasil:
Jumlah CD4 %CD4 Tanggal Test Tanggal Hasil Hemoglobin Tanggal Kunjungan
Terapi ARV
Tanggal Mulai ART Pemeriksaan Fisik
Infeksi Opportunistik
Jenis IO Tanggal Diagnosis
Kunjungan Ke- Alasan Kunjungan Darah
Hubungan Berat Badan
Kadar CD4+ Hasil Test Tanggal Test Tanggal Hasil
Supervisor ART atau Pengawas Minum Obat
Lampiran 5
HASIL OUTPUT STATA
Univariat
Age 31.7792 .3317989 31.12744 32.43095 Mean Std. Err. [95% Conf. Interval] Mean estimation Number of obs = 548 . mean Age Total 548 100.00 >32 213 38.87 100.00 <=32 335 61.13 61.13 Age2cat Freq. Percent Cum. . tab Age2cat
Total 548 100.00 missing 3 0.55 100.00 PS 147 26.82 99.45 other 398 72.63 72.63 ion Freq. Percent Cum. new_occupat . tab new_occupation Total 548 100.00 female 233 42.52 100.00 male 315 57.48 57.48 sex Freq. Percent Cum. . tab sex
Total 548 100.00
dont have 175 31.93 100.00 have 373 68.07 68.07 fARV Freq. Percent Cum. Supervisoro . tab SupervisorofARV Total 548 100.00 have 87 15.88 100.00 dont have 461 84.12 84.12 V Freq. Percent Cum. nstartingAR TypeofIOwhe . tab TypeofIOwhenstartingARV Total 548 100.00 elementary,no edu 264 48.18 100.00 jun,sen,col 284 51.82 51.82 edu2cat Freq. Percent Cum. . tab edu2cat Total 548 100.00 IDU 139 25.36 100.00 homosex 103 18.80 74.64 heteroNonPS 182 33.21 55.84 heteroPS 124 22.63 22.63 NewRisk2 Freq. Percent Cum. . tab NewRisk2
Total 548 100.00
lost to follow up 77 14.05 100.00 no lost to follow up 471 85.95 85.95 outcome Freq. Percent Cum. . tab outcome
Haemoglobin 12.73682 .0850218 12.56981 12.90384 Mean Std. Err. [95% Conf. Interval] Mean estimation Number of obs = 538 . mean Haemoglobin Total 548 100.00 . 10 1.82 100.00 >12 357 65.15 98.18 <=12 181 33.03 33.03 Hb2cat Freq. Percent Cum. . tab Hb2cat, missing
Weight 55.25627 .4480319 54.37618 56.13637 Mean Std. Err. [95% Conf. Interval] Mean estimation Number of obs = 542 . mean Weight Total 548 100.00 . 6 1.09 100.00 >55 232 42.34 98.91 <=55 310 56.57 56.57 W2cat Freq. Percent Cum. . tab W2cat, missing
Total 548 100.00 . 3 0.55 100.00 >=200 180 32.85 99.45 100-<200 132 24.09 66.61 <100 233 42.52 42.52 CD4100an Freq. Percent Cum. . tab CD4100an, missing
Insiden rate
total 1493.859001 .0515444 548 6.157426 . . time at risk rate subjects 25% 50% 75% incidence no. of Survival time origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. stsum
Bivariat
last observed exit t = 11.30459 earliest observed entry t = 0 1493.859 total analysis time at risk, at risk from t = 0 77 failures in single record/single failure data
548 obs. remaining, representing
0 exclusions
548 total obs.
origin: time dateof1stdayvisitYKP
t for analysis: (time-origin)/365.25 exit on or before: failure
obs. time interval: (origin, dateotthelastdayvisitingY] failure event: outcome == 1
. stset dateotthelastdayvisitingY, failure( outcome==1) origin( dateof1stdayvisitYKP) scale(365.25)
JENIS KELAMIN
sex 1.605116 .368226 2.06 0.039 1.023845 2.516394 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -435.52369 Prob > chi2 = 0.0386 LR chi2(1) = 4.28 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -435.52369 Refining estimates:
Iteration 2: log likelihood = -435.52369 Iteration 1: log likelihood = -435.52419 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox sex
female 42 6.3330 6.6319 4.9011 8.9739 male 35 8.6056 4.0671 2.9202 5.6646 sex D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
UMUR
_IAge2cat_2 .609908 .1585631 -1.90 0.057 .3664124 1.015216 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -435.71845 Prob > chi2 = 0.0487 LR chi2(1) = 3.89 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -435.71845 Refining estimates:
Iteration 3: log likelihood = -435.71845 Iteration 2: log likelihood = -435.71845 Iteration 1: log likelihood = -435.73007 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.Age2cat _IAge2cat_1-2 (naturally coded; _IAge2cat_1 omitted) . xi: stcox i.Age2cat
>32 20 5.4147 3.6936 2.3830 5.7252 <=32 57 9.5239 5.9850 4.6165 7.7590 Age2cat D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
PENDIDIKAN
edu2cat .8221985 .1883037 -0.85 0.393 .5248444 1.28802 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -437.29571 Prob > chi2 = 0.3920 LR chi2(1) = 0.73 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -437.29571 Refining estimates:
Iteration 2: log likelihood = -437.29571 Iteration 1: log likelihood = -437.29571 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox edu2cat
elementary,no edu 36 7.8458 4.5884 3.3098 6.3611 jun,sen,col 41 7.0928 5.7805 4.2563 7.8506 edu2cat D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
PEKERJAAN
_Inew_occup_99 1.479216 1.499579 0.39 0.699 .2028207 10.78824 _Inew_occup_2 1.688489 .3970441 2.23 0.026 1.064977 2.677049 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -435.27109 Prob > chi2 = 0.0915 LR chi2(2) = 4.78 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -435.27109 Refining estimates:
Iteration 3: log likelihood = -435.27109 Iteration 2: log likelihood = -435.27109 Iteration 1: log likelihood = -435.29552 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.new_occupat~n _Inew_occup_1-99 (naturally coded; _Inew_occup_1 omitted) . xi: stcox i.new_occupation
missing 1 0.1797 5.56359 0.78371 39.49636 PS 30 4.0864 7.34141 5.13301 10.49995 other 46 10.6724 4.31017 3.22843 5.75436 new_oc~n D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
.
new_occupation 1.689914 .3973969 2.23 0.026 1.065854 2.679363 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -429.27863 Prob > chi2 = 0.0292 LR chi2(1) = 4.75 Time at risk = 1475.88501
No. of failures = 76
No. of subjects = 545 Number of obs = 545 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -429.27863 Refining estimates:
Iteration 3: log likelihood = -429.27863 Iteration 2: log likelihood = -429.27863 Iteration 1: log likelihood = -429.30457 Iteration 0: log likelihood = -431.65521 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox new_occupation if new_occupation~=99
PENGAWAS MINUM OBAT
dont have 30 3.2418 9.2542 6.4704 13.2356 have 47 11.6968 4.0182 3.0190 5.3480 Supervi~V D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
_ISuperviso_2 2.042776 .4830546 3.02 0.003 1.285102 3.247163 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -433.3936 Prob > chi2 = 0.0035 LR chi2(1) = 8.54 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -433.3936 Refining estimates:
Iteration 3: log likelihood = -433.3936 Iteration 2: log likelihood = -433.39361 Iteration 1: log likelihood = -433.51158 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.Supervisoro~V _ISuperviso_1-2 (naturally coded; _ISuperviso_1 omitted) . xi: stcox i.SupervisorofARV
CD4 >=200 29 4.2327 6.8513 4.7611 9.8592 100-<200 20 4.1524 4.8164 3.1074 7.4655 <100 28 6.4031 4.3729 3.0193 6.3333 CD4100an D Y Rate Lower Upper (545 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
CD4100an 1.226311 .1646613 1.52 0.129 .9425551 1.595492 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -435.82328 Prob > chi2 = 0.1291 LR chi2(1) = 2.30 Time at risk = 1478.830938
No. of failures = 77
No. of subjects = 545 Number of obs = 545 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -435.82328 Refining estimates:
Iteration 2: log likelihood = -435.82328 Iteration 1: log likelihood = -435.82348 Iteration 0: log likelihood = -436.97509 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox CD4100an if CD4100an~=999
_ICD4100an_3 1.503239 .3994009 1.53 0.125 .8930368 2.530386 _ICD4100an_2 1.130838 .3313503 0.42 0.675 .6367768 2.00823 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -435.77452 Prob > chi2 = 0.3010 LR chi2(2) = 2.40 Time at risk = 1478.830938
No. of failures = 77
No. of subjects = 545 Number of obs = 545 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -435.77452 Refining estimates:
Iteration 3: log likelihood = -435.77452 Iteration 2: log likelihood = -435.77452 Iteration 1: log likelihood = -435.77968 Iteration 0: log likelihood = -436.97509 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.CD4100an _ICD4100an_1-3 (naturally coded; _ICD4100an_1 omitted) . xi: stcox i.CD4100an
BERAT BADAN
_IW2cat_2 .8137962 .1984743 -0.84 0.398 .5045668 1.31254 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -420.43852 Prob > chi2 = 0.3938 LR chi2(1) = 0.73 Time at risk = 1474.521561
No. of failures = 74
No. of subjects = 542 Number of obs = 542 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -420.43852 Refining estimates:
Iteration 2: log likelihood = -420.43852 Iteration 1: log likelihood = -420.43872 Iteration 0: log likelihood = -420.80215 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.W2cat _IW2cat_1-2 (naturally coded; _IW2cat_1 omitted) . xi: stcox i.W2cat
>55 26 5.7315 4.5363 3.0887 6.6625 <=55 48 9.0137 5.3252 4.0131 7.0664 W2cat D Y Rate Lower Upper (542 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
W2cat .8137962 .1984743 -0.84 0.398 .5045668 1.31254 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -420.43852 Prob > chi2 = 0.3938 LR chi2(1) = 0.73 Time at risk = 1474.521561
No. of failures = 74
No. of subjects = 542 Number of obs = 542 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -420.43852 Refining estimates:
Iteration 2: log likelihood = -420.43852 Iteration 1: log likelihood = -420.43872 Iteration 0: log likelihood = -420.80215 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox W2cat if W2cat~=999
HEMOGLOBIN
_IHb2cat_2 .7845558 .1881889 -1.01 0.312 .4902852 1.255448 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -412.43031 Prob > chi2 = 0.3162 LR chi2(1) = 1.00 Time at risk = 1462.548939
No. of failures = 73
No. of subjects = 538 Number of obs = 538 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -412.43031 Refining estimates:
Iteration 2: log likelihood = -412.43031 Iteration 1: log likelihood = -412.43092 Iteration 0: log likelihood = -412.93251 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.Hb2cat _IHb2cat_1-2 (naturally coded; _IHb2cat_1 omitted) . xi: stcox i.Hb2cat
Hb2cat .7845558 .1881889 -1.01 0.312 .4902852 1.255448 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -412.43031 Prob > chi2 = 0.3162 LR chi2(1) = 1.00 Time at risk = 1462.548939
No. of failures = 73
No. of subjects = 538 Number of obs = 538 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -412.43031 Refining estimates:
Iteration 2: log likelihood = -412.43031 Iteration 1: log likelihood = -412.43092 Iteration 0: log likelihood = -412.93251 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
. xi: stcox Hb2cat if Hb2cat~=999
_IHb2cat_2 .7845558 .1881889 -1.01 0.312 .4902852 1.255448 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -412.43031 Prob > chi2 = 0.3162 LR chi2(1) = 1.00 Time at risk = 1462.548939
No. of failures = 73
No. of subjects = 538 Number of obs = 538 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -412.43031 Refining estimates:
Iteration 2: log likelihood = -412.43031 Iteration 1: log likelihood = -412.43092 Iteration 0: log likelihood = -412.93251 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.Hb2cat _IHb2cat_1-2 (naturally coded; _IHb2cat_1 omitted) . xi: stcox i.Hb2cat
INFEKSI OPORTUNISTIK
_ITypeofIOw_2 .6596046 .2340774 -1.17 0.241 .3290131 1.322373 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -436.89812 Prob > chi2 = 0.2164 LR chi2(1) = 1.53 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -436.89812 Refining estimates:
Iteration 3: log likelihood = -436.89812 Iteration 2: log likelihood = -436.89813 Iteration 1: log likelihood = -436.91033 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.TypeofIOwhe~V _ITypeofIOw_1-2 (naturally coded; _ITypeofIOw_1 omitted) . xi: stcox i.TypeofIOwhenstartingARV
have 9 2.5698 3.5022 1.8223 6.7310 dont have 68 12.3688 5.4977 4.3347 6.9728 TypeofI~V D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
FAKTOR RISIKO PENULARAN Prob > chi2 = 0.0035 chi2( 3) = 13.61 ( 3) _INewRisk2_4 = 0 ( 2) _INewRisk2_3 = 0 ( 1) _INewRisk2_2 = 0 . testparm _INewRisk2* _INewRisk2_4 .308768 .1099012 -3.30 0.001 .1536952 .6203035 _INewRisk2_3 1.141577 .3688715 0.41 0.682 .605984 2.150549 _INewRisk2_2 .8119563 .2331612 -0.73 0.468 .4624894 1.425488 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -429.46201 Prob > chi2 = 0.0009 LR chi2(3) = 16.40 Time at risk = 1493.859001
No. of failures = 77
No. of subjects = 548 Number of obs = 548 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -429.46201 Refining estimates:
Iteration 3: log likelihood = -429.46201 Iteration 2: log likelihood = -429.46272 Iteration 1: log likelihood = -429.7365 Iteration 0: log likelihood = -437.66205 origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
i.NewRisk2 _INewRisk2_1-4 (naturally coded; _INewRisk2_1 omitted) . xi: stcox i.NewRisk2
IDU 12 5.7302 2.0942 1.1893 3.6875 homosex 16 1.7679 9.0502 5.5445 14.7727 heteroNonPS 24 3.9662 6.0511 4.0558 9.0278 heteroPS 25 3.4742 7.1959 4.8623 10.6494 NewRisk2 D Y Rate Lower Upper (548 records included in the analysis)
Estimated rates (per 100) and lower/upper bounds of 95% confidence intervals origin: time dateof1stdayvisitYKP
analysis time _t: (dateotthelastdayvisitingY-origin)/365.25 failure _d: outcome == 1
Multivariat _ICD4100an_3 1.052746 .2974222 0.18 0.856 .6051209 1.831494 _ICD4100an_2 1.013407 .3033473 0.04 0.965 .5636251 1.822123 _IAge2cat_2 .5800395 .1544525 -2.05 0.041 .3441915 .9774959 _INewRisk2_4 .4839525 .3408563 -1.03 0.303 .1216988 1.924505 _INewRisk2_3 1.628288 .9856226 0.81 0.421 .4971513 5.333028 _INewRisk2_2 1.108921 .7026314 0.16 0.870 .3203058 3.839163 _ISuperviso_2 1.824912 .4458583 2.46 0.014 1.13052 2.945815 _Inew_occup_99 1.08224 1.128272 0.08 0.940 .1402546 8.35084 _Inew_occup_2 1.071217 .5844343 0.13 0.900 .3676877 3.120871 _Isex_2 1.429216 .5020292 1.02 0.309 .7179651 2.845068 _t Haz. Ratio Std. Err. z P>|z| [95% Conf. Interval] Log likelihood = -423.05146 Prob > chi2 = 0.0019 LR chi2(10) = 27.85 Time at risk = 1478.830938
No. of failures = 77
No. of subjects = 545 Number of obs = 545 Cox regression -- Breslow method for ties
Iteration 0: log likelihood = -423.05146 Refining estimates:
Iteration 3: log likelihood = -423.05146 Iteration 2: log likelihood = -423.05232 Iteration 1: log likelihood = -423.50887