| Literature DB >> 30944390 |
Florian Moik1,2, Jakob M Riedl1, Thomas Winder3, Angelika Terbuch1, Christopher H Rossmann1, Joanna Szkandera1, Thomas Bauernhofer1, Anne-Katrin Kasparek1, Renate Schaberl-Moser1, Andreas Reicher1,4, Felix Prinz1, Martin Pichler1,5, Herbert Stöger1, Michael Stotz1, Armin Gerger1,6, Florian Posch7,8.
Abstract
Whether 2nd-line-chemotherapy (2LCTX) + best-supportive-care (BSC) benefits patients with advanced biliary tract cancer (aBTC) more than BSC alone is unclear. We therefore conducted a propensity-score-based comparative effectiveness analysis of overall survival (OS) outcomes in 80 patients with metastatic, recurrent, or inoperable aBTC, of whom 38 (48%) were treated with BSC + 2LCTX and 42 (52%) with BSC alone. After a median follow-up of 14.8 months and 49 deaths, the crude 6-, 12-, and 18-month Kaplan-Meier OS estimates were 77%, 53% and 23% in the BSC + 2LCTX group, and 29%, 21%, and 14% in patients in the BSC group (p = 0.0003; Hazard ratio (HR) = 0.36, 95%CI:0.20-0.64, p = 0.001). An inverse-probability-of-treatment-weighted (IPTW) analysis was conducted to rigorously account for the higher prevalence of favorable prognostic variables in the 2LCTX + BSC group. After IPTW-weighting, the favorable association between 2LCTX and OS prevailed (adjusted HR = 0.40, 95%CI: 0.17-0.95, p = 0.037). IPTW-weighted 6-, 12-, and 18-month OS estimates were 77%, 58% and 33% in the BSC + 2LCTX group, and 39%, 28% and 22% in the BSC group (p = 0.037). Moreover, the benefit of 2LCTX was consistent across several clinically-relevant subgroups. Within the limitations of an observational study, these findings support the concept that 2LCTX + BSC is associated with an OS benefit over BSC alone in aBTC.Entities:
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Year: 2019 PMID: 30944390 PMCID: PMC6447553 DOI: 10.1038/s41598-019-42069-1
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Baseline characteristics of the study population (n = 80).
| Variable | n (% miss.) | Overall (n = 80) | BSC only (n = 42) | 2LCTX + BSC (n = 38) | p* | ΔS | ΔS-IPTW_20 | ΔS-IPTW_8 |
|---|---|---|---|---|---|---|---|---|
|
| ||||||||
| Age (years) | 80 (0%) | 68.0 [60.9–73.0] | 69.5 [63.0–73.7] | 67.1 [57.5–72.3] | 0.16 | 0.26 | 0.27 | 0.30 |
| Female Gender | 80 (0%) | 38 (48%) | 24 (57%) | 14 (37%) | 0.07 | 0.41 | 0.02 | 0.05 |
| BMI (kg/m²) | 70 (13%) | 24.4 [22.3–26.9] | 24.0 [21.8–27.1] | 24.8 [22.4–26.6] | 0.49 | 0.15 | 0.03 | 0.17 |
| History of smoking | 72 (10%) | 19 (26%) | 11 (31%) | 8 (22%) | 0.42 | 0.19 | 0.16 | 0.06 |
| Charleson Comorbidity Index | 80 (0%) | 8 [7–10] | 9 [7–10] | 8 [7–9] | 0.69 | 0.02 | 0.03 | 0.06 |
| Synchronous aBTC | 71 (12%) | 36 (51%) | 10 (29%) | 24 (71%) | 0.001 | 0.83 | 0.43 | 0.21 |
|
| 60 (25%) | / | / | / | / | / | / | |
| Karnofksy Index | / | 90 [80–90] | 80 [70–90] | 90 [80–90] | 0.0001 | 1.21 | 0.31 | 0.59 |
| –ECOG 0 | / | 33 (55%) | 10 (34%) | 23 (74%) | 0.002 | 0.85 | 0.23 | 0.24 |
| –ECOG 1–2 | / | 27 (45%) | 19 (66%) | 8 (26%) | ||||
|
| 80 (0%) | / | / | / | / | / | / | |
| –Gallbladder | / | 23 (29%) | 17 (40%) | 6 (16%) | 0.006 | 0.56 | 0.04 | 0.12 |
| –Intrahepatic | / | 30 (38%) | 17 (40%) | 13 (34%) | 0.13 | 0.08 | 0.18 | |
| –Perihilar/Klatskin | / | 9 (11%) | 2 (5%) | 7 (18%) | 0.43 | 0.48 | 0.22 | |
| –Distal/Ampulla | / | 14 (18%) | 3 (7%) | 11 (29%) | 0.58 | 0.43 | 0.18 | |
| –CUP-CCC | / | 4 (5%) | 3 (7%) | 1 (3%) | 0.21 | 0.72 | 0.40 | |
|
| 80 (0%) | / | / | / | / | / | / | |
| –Adenocarcinoma | / | 78 (98%) | 41 (98%) | 37 (98%) | 0.99 | 0.02 | 0.03 | 0.01 |
| –Others | / | 2 (3%) | 1 (2%) | 1 (3%) | ||||
|
| 75 (6%) | / | / | / | / | / | / | |
| –G1 or G2 | / | 46 (61%) | 22 (56%) | 24 (67%) | 0.60 | 0.21 | 0.14 | 0.41 |
| –G3 | / | 29 (57%) | 17 (44%) | 12 (33%) | ||||
|
| 80 (0%) | / | / | / | / | / | / | |
| –Cisplatin/Gemcitabine | / | 20 (25%) | 10 (24%) | 10 (26%) | 0.47 | 0.06 | 0.28 | 0.44 |
| –Gemcitabine mono | / | 45 (56%) | 26 (62%) | 19 (50%) | 0.24 | 0.39 | 0.31 | |
| –Other CTX regimens | / | 15 (19%) | 6 (14%) | 9 (24%) | 0.24 | 0.18 | 0.13 | |
| Objective response | 80 (0%) | 16 (20%) | 8 (19%) | 8 (21%) | 0.82 | 0.05 | 0.09 | 0.21 |
| Number of cycles | 79 (1%) | 4 [2–6] | 3 [2–6] | 4 [3–5] | 0.10 | 0.36 | 0.45 | 0.48 |
|
| 38 (0%) | / | / | / | / | / | / | |
| –Fluoropyrimidine mono | / | N/A | N/A | 26 (68%) | N/A | N/A | N/A | N/A |
| –Fluoropyrimidine-based combinations | / | N/A | N/A | 8 (21%) | N/A | N/A | N/A | N/A |
| –Other CTX regimens | / | N/A | N/A | 4 (11%) | N/A | N/A | N/A | N/A |
| Objective response rate | 38 (0%) | N/A | N/A | 1 (3%) | N/A | N/A | N/A | N/A |
| Number of cycles | 36 (5%) | N/A | N/A | 4 [2–8] | N/A | N/A | N/A | N/A |
|
| / | / | / | / | / | / | / | |
| Haemoglobin (g/dL) | 78 (3%) | 11.7 [10.1–12.6] | 10.2 [9.8–12.1] | 12.4 [11.3–13.1] | 0.002 | 0.62 | 0.57 | 0.64 |
| Leukocyte count (G/L) | 78 (3%) | 7.4 [5.2–9.4] | 7.7 [5.7–10.4] | 6.9 [5.1–9.1] | 0.26 | 0.39 | 0.03 | 0.44 |
| Neutrophil count (G/L) | 78 (3%) | 4.8 [3.0–6.4] | 5.5 [3.5–8.3] | 4.4 [2.8–5.4] | 0.06 | 0.41 | 0.39 | 0.10 |
| Lymphocyte count (G/L) | 78 (3%) | 1.4 [1.1–1.7] | 1.3 [0.9–1.7] | 1.4 [1.1–2.1] | 0.12 | 0.47 | 0.30 | 0.17 |
| Platelet count (G/L) | 78 (3%) | 225 [138–343] | 225 [134–307] | 224 [141–428] | 0.45 | 0.33 | 0.18 | 0.11 |
| C-reactive protein (mg/dL) | 77 (4%) | 21.6 [7.7–47.1] | 32.5 [11.4–62.0] | 12.6 [5.2–34.2] | 0.03 | 0.45 | 0.15 | 0.41 |
| Bilirubin (mg/dL) | 77 (4%) | 0.6 [0.4–1.3] | 0.8 [0.4–2.0] | 0.5 [0.4–0.9] | 0.06 | 0.49 | 0.19 | 0.44 |
| Gamma-GT (units/L) | 77 (4%) | 311 [102–577] | 336 [99–613] | 245 [113–394] | 0.43 | 0.12 | 0.23 | 0.18 |
| Alkalic Phosphatase (units/L) | 77 (4%) | 168 [106–352] | 208 [113–378] | 152 [96–268] | 0.32 | 0.34 | 0.01 | 0.27 |
| AST (units/L) | 77 (4%) | 46 [30–80] | 47 [33–83] | 37 [27–66] | 0.12 | 0.38 | 0.30 | 0.39 |
| ALT (units/L) | 77 (4%) | 34 [20–62] | 34 [19–70] | 32 [20–59] | 0.74 | 0.16 | 0.04 | 0.07 |
| Albumin (g/dL) | 77 (4%) | 3.7 [3.2–4.0] | 3.4 [2.9–3.9] | 3.9 [3.6–4.1] | 0.0007 | 0.63 | 0.52 | 0.70 |
| CEA | 48 (40%) | 3.6 [1.8–11.0] | 4.3 [1.8–11.1] | 3.4 [1.9–10.9] | 0.98 | 0.12 | 0.08 | 0.10 |
| CA19–9 | 48 (40%) | 144 [21–944] | 223 [14–3204] | 97 [29–433] | 0.56 | 0.21 | 0.14 | 0.34 |
Distribution overall and by treatment assignment to 2LCTX + BSC versus BSC. Continuous variables are summarized as medians [25th percentile (Q1) – 75th percentile (Q3)], whereas categorical variables are reported as absolute frequencies and percentages. *p-values for difference between 2LCTX + BSC vs. BSC alone are from Pearson’s chi-squared tests (categorical variables with expected cell counts ≥5), Fisher’s exact tests (categorical variables with expected cell counts < 5), or Wilcoxon rank-sum tests (continuous variables); Abbreviations: n (%miss.) – number of patients with fully observed data (% missing from a total of 80 patients), BSC – best supportive care, 2LCTX + BSC – 2nd-line chemotherapy and BSC, ΔS – Standardized mean difference (SMD), ΔS-IPTW_20 – IPTW-weighted SMD (weighing with the main IPTW based on a 20-variable propensity score model as reported in Supplementary Table 2), ΔS-IPTW_8 – IPTW-weighted SMD (weighing with the “sensitivity analysis” IPTW based on an 8-variable propensity score model as reported in Supplementary Table 3), BMI – body mass index, ECOG – Eastern Cooperative Oncology Group performance status, CUP-CCC – cancer of unknown primary with cholangiocellular differentiation, CTX – chemotherapy, AST – Aspartate aminotransferase, ALT – Alanine aminotransferase, CEA – carcinoembryonic antigen, CA 19–9 – Cancer antigen 19–9.
Figure 1Unadjusted Kaplan-Meier curves of overall survival according to treatment assignment to 2LCTX + BSC versus BSC alone. Abbreviations: 2LCTX – 2nd-line chemotherapy, BSC – best supportive care.
Figure 2IPTW-weighted Kaplan-Meier curves of overall survival according to treatment assignment to 2LCTX + BSC versus BSC alone. *Number of patients represent the number in the synthetic pseudo-population generated by the IPTW. Abbreviations: IPTW – Inverse probability of treatment weight, 2LCTX – 2nd-line chemotherapy, BSC – best supportive care.
Figure 3Hazards of death-from-any-cause according to treatment assignment to 2LCTX + BSC vs. BSC alone. Hazard curves were predicted from a flexible parametric survival model (log(cumulative hazard) scale) with 3 degrees of freedom for the time-invariant treatment variable and 2 degrees of freedom for the time-varying treatment variable. Abbreviations: 2LCTX – 2nd-line chemotherapy, BSC – best supportive care.
Figure 4Predicted probability of overall survival according to treatment assignment to 2LCTX + BSC vs. BSC alone. Survival curves were predicted from a flexible parametric survival model (log(cumulative hazard) scale) with 3 degrees of freedom for the time-invariant treatment variable and 2 degrees of freedom for the time-varying treatment variable. Abbreviations: 2LCTX – 2nd-line chemotherapy, BSC – best supportive care.
Subgroup analyses of 2LCTX benefit in aBTC Table 2.
| Hazard ratio | 95%CI | Interaction p-value | |
|---|---|---|---|
| ECOG: 0 | 0.89 | 0.24–3.39 | 0.237 |
| ECOG: 1–2 | 0.37 | 0.13–1.08 | |
| Synchronous aBTC | 0.30 | 0.07–1.20 | 0.524 |
| Metachronous aBTC | 0.45 | 0.16–1.24 | |
| No response during 1stline CTX | 0.41 | 0.16–1.04 | 0.159 |
| Response during 1stline CTX | 0.24 | 0.03–1.73 | |
| Bilirubin ≤ 50th percentile | 0.40 | 0.13–1.25 | 0.813 |
| Bilirubin > 50th percentile | 0.58 | 0.24–1.36 | |
| C-reactive protein ≤ 50th percentile | 0.54 | 0.15–1.88 | 0.349 |
| C-reactive protein > 50th percentile | 0.32 | 0.15–0.70 | |
| aBTC: Gallbladder | 0.05 | 0.01–0.39 | 0.020 |
| aBTC: Intrahepatic CCC | 0.64 | 0.22–1.88 | |
| aBTC: Others | 1.08 | 0.28–4.24 |
Subgroup analyses of 2LCTX benefit in aBTC. Hazard ratios and interaction p-values were derived from IPTW-weighted Cox regression models of overall survival. Abbreviations: 2LCTX – 2nd-line chemotherapy, aBTC – Advanced biliary tract cancer, 95%CI – 95% confidence interval, ECOG – Eastern Cooperative Oncology Group performance status, CTX - chemotherapy
Figure 5Time-to-progression (TTP) in the 2LCTX + BSC group (n = 38). TTP with 95% confidence bands (gray shadowing) was estimated with an inverse Kaplan-Meier estimator.