Post-Randomization vs On Treatment Made All the Difference

The Food and Drug Administration (FDA) recently requested withdraw of Belviq® and Belviq XR® (lorcaserin and extended-release lorcaserin) from the U.S. market.

When the FDA publishes a note in the New England Journal of Medicine, I pay attention to it. There are many lessons to learn, but also some questions to ask. On this occasion, the FDA explains why a product had to be withdrawn from the market, based, among other issues, on the detection of a safety signal for cancer. The signal appeared from a phase 4 study designed to address cardiovascular safety (MACE).

The following is a short timeline which can help us understand the course of events:

• December 2009: the applicant submits marketing application for lorcaserin. The FDA did not approve it, in part due to non-clinical carcinogenicity studies revealing and increased incidence of tumors in rats exposed to the drug.
• December 2011: the applicant submitted additional non-clinical and clinical data.
• May 2012: FDA approval, with the condition of conducting a postmarketing study focusing on cardiovascular safety.
• 2014 to 2018: CAMELLIA-TIMI 61 trial was conducted.

Subsequently, the FDA performed a safety analysis of the study and identified a potential signal of increased cancers and cancer-related mortality:

“In contrast to the published study, when assessing cancer incidence, the FDA considered all postrandomization adverse events, not just ‘on treatment’ events.”

Demographic and clinical variables were balanced between the treatment groups at baseline and during the course of the study.

This was a long-latency safety signal, in which cancer numbers were elevated for lorcaserin for all latency periods beyond 180 days. The number of new cancer cases was similar in the two treatment groups for the first 180 days.

Benefit-Risk Evaluation

The FDA weighed the drug’s benefits against the excess cancer risk. The difficulty of mitigating that risk, and the uncertain clinical benefit led them to conclude that the benefits do not outweigh the risks.

To provide a little more context, following are some highlights from the U.S. label and from the trial:

Lorcaserin FDA Label

In the U.S. package insert there is no mention of cancer on the Adverse Reactions section. However, in section 13: Nonclinical Toxicology, Carcinogenesis subsection, it is stated:

• Increase in mammary adenocarcinoma in female rats
• Increase in mammary fibroadenoma in female rats at all doses
• In male rats, treatment-related neoplastic changes in different organs

The CAMELLIA-TIMI 61 Trial

Title: A Study to Evaluate the Effect of Long-term Treatment With BELVIQ (Lorcaserin HCl) on the Incidence of Major Adverse Cardiovascular Events and Conversion to Type 2 Diabetes Mellitus in Obese and Overweight Subjects With Cardiovascular Disease or Multiple Cardiovascular Risk Factors (CAMELLIA-TIMI).

Arm/Group description: Participants received lorcaserin HCL 10 mg or lorcaserin HCL placebo-matching , tablets, orally, twice daily for up to 52 months.

Adverse Events Time Frame: From baseline up to 30 days after last dose of study drug (approximately 56 months). This constitutes the “On-Treatment plus 30 days analysis set”.

Study-Specific Events: Malignant neoplasms (with the exception of basal cell and squamous cell carcinomas of the skin), among others, were considered study-specific events, per protocol.

Comments

The following are my personal, independent thoughts.

Even though there were non-clinical results possibly indicating a higher risk of neoplasms, the end result was very difficult (if not impossible) to predict. The phase 4 study was designed with the specific purpose of responding to the cardiovascular safety question. In spite of that, cancer-related adverse events were given special attention in the protocol, but this was not enough for them to detect a safety concern. Twelve-thousand patients were studied, however the 95% CIs for the rate ratios were still not clearly statistically significant.

Should all studies analyzing products with a potential risk of causing cancer, allow for sufficient follow-up time as to reduce attrition risk?

Could an analysis of FAERS data have revealed that signal earlier?

Treatment and placebo groups were well balanced in terms of demographic characteristics and some clinically and epidemiologically relevant risk factors, which is expected.

But, what about the analysis of potential differences between patients who acquired cancer and those who didn’t? This is not going to change the outcome, obviously. But machine learning techniques applied to these safety data could help understand the differences between the 2 groups (cancer vs no cancer), both in treatment and placebo arms. The knowledge gained as a result could open our minds to a whole world of possibilities.