You will be shown a paragraph from a biomedical research article. Your task is to extract all drug combinations appearing in a specific sentence within in the paragraph. Each drug combination should be assigned to one of the following three categories:

- POS: Indicates a positive interaction between the drugs in the combination; for instance, drugs that have an additive or synergistic effect.
- NEG: Indicates a negative interaction between the drugs in the combination; for instance, combining these drugs might result in adverse side effects, or might reduce their efficacy.
- COMB: Indicates that the drugs are given in combination, but the type of interaction between the drugs cannot be determined based on the provided context.

Please format your answer as a json array. Each entry in the array should itself be an array formatted as [<drug_1>, <drug_2>, ..., <drug_n>, <category>] where <category> is one of the three categories listed above and <drug_1>, ..., <drug_n> are drug names copied verbatim from the input sentence. Different combinations may involve different numbers of drugs; in other words, the `n` in <drug_n> may vary.

As an example, the following output describes two extracted drug combinations; one between two drugs, and one between three drugs:

[["artesunate", "artemether", "COMB"], ["Nifedipine", "Labetalol", "Prazosin", "POS"]]

The paragraph and specific sentence are below. You should only extract relationships expressed in the specific sentence; the paragraph is provided for context.

In your output, return only the json array and no other text. If no drug combinations appear, return an empty array `[]`.

paragraph: Altered treatment of chronic lymphocytic leukemia in Germany during the last decade. Chronic lymphocytic leukemia (CLL) is the most common subtype of adult leukemia in the western world. We here report a nationwide survey monitoring the treatment decisions concerning CLL patients in Germany in 2011 and compare treatment trends to sequential surveys performed previously during the last decade. The rate of patients diagnosed in early stages (Binet A/B) notably increased (2006: 66 %, 2009: 71 %, 2011: 77 %) over the years. From 2006 to 2009, the most frequent applied regime switched from chlorambucil to fludarabine containing regimes (2006 chlorambucil: 32 %, 2009: 14 %, fludarabine 2006: 23 %, 2009: 37 %). In 2011 , the combination of rituximab with bendamustine ( 31 % ) was most frequent used followed by the rituximab-fludarabine-cyclophosphamide ( 22 % ) regime . Further, immune-chemotherapies were administered significantly more often over the observation period (2006: 15 %, 2011: 73 %). Taken together, this data reflects the change of treatment strategies over the last decade in clinical reality.

sentence: In 2011 , the combination of rituximab with bendamustine ( 31 % ) was most frequent used followed by the rituximab-fludarabine-cyclophosphamide ( 22 % ) regime .
[["rituximab", "bendamustine", "POS"]]