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. Author manuscript; available in PMC: 2012 Oct 18.
Published in final edited form as: JAMA. 2012 Apr 18;307(15):1593–1601. doi: 10.1001/jama.2012.454

Table 2.

Impact of Bevacizumab in addition to Carboplatin and Paclitaxel on Hazard Ratios for Overall Survival

Model Sample Size
Hazard Ratio (95% CI)
BCP, CP 2006–7 BCP, CP 2002–5 BCP vs. CP 2006–7 BCP vs. CP 2002–5
Unadjusted model 318, 1,182 318, 2,664 1.00 (0.88–1.14) 0.95 (0.84–1.08)

Multivariable adjusted model a 318, 1,182 318, 2,664 1.01 (0.88–1.15) 0.94 (0.83–1.06)

Propensity score-adjusted model b

 Stratification 318, 1,153 311, 2,512 1.01 (0.89–1.16) 0.93 (0.83–1.06)

 Within propensity score quintile

  1 (lowest propensity) 33, 261 51, 716 0.75 (0.51–1.10) 0.97 (0.72–1.30)

  2 69, 337 84, 795 1.06 (0.80–1.39) 0.92 (0.73–1.17)

  3 110, 361 107, 640 1.06 (0.85–1.32) 0.97 (0.79–1.20)

  4 78, 151 52, 299 1.16 (0.87–1.55) 0.81 (0.59–1.11)

  5 (highest propensity) 28, 43 17, 62 0.84 (0.48–1.47) 1.07 (0.61–1.91)

 Regression adjustment 318, 1,153 311, 2,512 1.01 (0.89–1.16) 0.94 (0.83–1.06)

 Weighting (stabilized IPTW) 318, 1,153 311, 2,512 0.99 (0.87–1.13) 0.93 (0.82–1.06)

 Matching 1:1 318, 318 318, 318 0.99 (0.79–1.23) 0.90 (0.72–1.13)

Subgroup analyses


 Stage IV c 262, 838 262, 1,848 0.96 (0.83–1.12) 0.88 (0.77–1.02)

 Estimated comorbidity score of 0 d 210, 665 210, 1,661 1.04 (0.87–1.23) 0.92 (0.79–1.08)

Sensitivity analyses a

 Patients surviving >8 days from treatment start 315, 1,173 315, 2,637 1.00 (0.87–1.15) 0.91 (0.80–1.03)

 Patients first treated with bevacizumab between 1 and 30 days of starting CP and surviving >30 days from treatment start 342, 1,068 342, 2,478 0.98 (0.86–1.12) 0.89 (0.79–1.01)

Abbreviations: CI, confidence interval; BCP, bevacizumab-carboplatin-paclitaxel; CP 2006–7, carboplatin-paclitaxel (diagnoses 2006–7 when bevacizumab was FDA approved for NSCLC); CP 2002–5, carboplatin-paclitaxel (diagnoses 2002–5 when bevacizumab was not available (2002–3) or not approved for NSCLC treatment); IPTW, inverse probability of treatment weighting.

a

The model was adjusted for baseline age, sex, race/ethnicity, marital status, geographic region, urban residency, tumor grading, census tract education, median income, modified Charlson comorbidities, and AJCC stage.

b

The propensity of receiving BCP was estimated using multivariable logistic regression model that included baseline age, sex, race/ethnicity, marital status, geographic region, urban residency, tumor grading, census tract education, median income, modified Charlson comorbidities, and AJCC stage.

c

The model was adjusted for baseline age, sex, race/ethnicity, marital status, geographic region, urban residency, tumor grading, census tract education, median income, and modified Charlson comorbidities.

d

The model was adjusted for baseline age, sex, race/ethnicity, marital status, geographic region, urban residency, tumor grading, census tract education, median income, and AJCC stage.