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: The impact of fewer hip fractures with risedronate versus alendronate in the first year of treatment: modeled German cost-effectiveness analysis. The risedronate and alendronate (REAL) cohort study provides unique comparative effectiveness data for real world bisphosphonate treatment of osteoporosis. ### objective The objective of this analysis was to assess the cost-effectiveness of risedronate compared to generic alendronate in Germany applying the REAL effectiveness data . ### Materials And Methods A validated Markov model of osteoporosis was populated with REAL effectiveness data and German epidemiological, cost, and utility data. To estimate the impact of therapy on hip fractures, costs, and quality adjusted life years (QALYs), the analysis included women>or=65 years, treated with risedronate or alendronate and followed for 4 additional years. Country-specific data included population mortality, fracture costs, and annual drug costs, using a German social insurance perspective. Costs and outcomes were discounted at 3%. A differential hip fracture relative risk reduction of 43% was applied to risedronate vs. alendronate. ### results The model predicted that treatment with risedronate would result in fewer hip fractures and more QALYs at a reduced cost (savings of euro278 per treated woman) compared to treatment with generic alendronate. Sensitivity analysis assuming 2 years of treatment and equivalence of effect after 1 year show cost savings as well (euro106 per treated woman). ### discussion Whereas previous economic evaluations involving bisphosphonates have mainly relied on efficacy data from noncomparative clinical trials, this study's strength is in the use of comparative effectiveness data from one data source. The magnitude of the cost savings observed were sensitive to alternative assumptions regarding treatment duration, therapy discontinuation and cost of generic alendronate. ### conclusions Based on "real world" data the analysis supports the first line use of risedronate for the treatment of osteoporotic women in Germany.

sentence: The objective of this analysis was to assess the cost-effectiveness of risedronate compared to generic alendronate in Germany applying the REAL effectiveness data .
[]