Chemotherapy for Late-Stage Cancer Patients: Meta-Analysis of Complete Response Rates

Abstract

Complete response (CR) rates reported for cytotoxic chemotherapy for late-stage cancer patients are generally low, with few exceptions, regardless of the solid cancer type or drug regimen. We investigated CR rates reported in the literature for clinical trials using chemotherapy alone, across a wide range of tumour types and chemotherapeutic regimens, to determine an overall CR rate for late-stage cancers. A total of 141 reports were located using the PubMed database. A meta-analysis was performed of reported CR from 68 chemotherapy trials (total 2732 patients) using standard agents across late-stage solid cancers-a binomial model with random effects was adopted. Mean CR rates were compared for different cancer types, and for chemotherapeutic agents with different mechanisms of action, using a logistic regression. Our results showed that the CR rates for chemotherapy treatment of late-stage cancer were generally low at 7.4%, regardless of the cancer type or drug regimen used. We found no evidence that CR rates differed between different chemotherapy drug types, but amongst different cancer types small CR differences were evident, although none exceeded a mean CR rate of 11%. This remarkable concordance of CR rates regardless of cancer or therapy type remains currently unexplained, and motivates further investigation.

Keywords: Advanced Cancer; Chemotherapy; Complete Response Rates; Meta-analysis; Metastatic Cancer.

Figure 1.. Funnel plot to check for publication bias.

For each of the 68 chemotherapy trials, the size N of the cohort is plotted on the vertical axis. On the horizontal axis the fraction of the cohort that displayed complete response (CR) is plotted. The red vertical line represents the average of the CR fraction = 0.0706, which corresponds to 7.06%. A standard deviation each side of the average is represented by the curved red lines, calculated by assuming a binomial model. The points appear to be clustered in bands, due to the affect of data quantisation—this is due to the fact that integer numbers of patients have a CR. Thus the first band of points, toward the bottom left of the graph, represent all the trials with a total CR = 1 person, the next band represents all the trials with total CR = 2 people, and so on. For higher total CR numbers, the bands do not appear due to the sparsity of data for large trials. On the funnel plot we see a large spread in CR fraction for 6 trials that are optimistically over a standard deviation, however, the overall skew is nevertheless small. Thus the effects of publication bias appear to be minimal for this study.

Figure 2.. Flow chart summarizing the literature search and study selection for the meta-analysis.

The final 68 studies represented a total of 2732 patients.

Figure 3.. Estimates (red points) and 95% confidence intervals (grey bars) for meta-analyses.

These are for ( a) Cancer type (SCCa = Squamous cell carcinoma; RCC = renal cell carcinoma; NSCLC = non-small cell lung carcinoma) and by ( b) Primary drug type, (abbreviation key; TPI = Topoisomerase inhibitor, TCCi = T-Cell Cytokine inhibitor (Cyclosporine), SP = Spindle poison, NA = Nucleoside analogue, DRsi = DNA/RNA synthesis inhibitor, AM = Antimetabolite, ALK = Alkylating Agent, AB = Antibiotic). The thin vertical blue line denotes a 7.4% CR rate, which is the overall estimate from the meta-analysis.