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: Association of HER-2 copy number and HER-2/CEP-17 ratio with neoadjuvant taxane-containing chemotherapy sensitivity in locally advanced breast cancer. Aneusomy 17 causes inconsistency in fluorescence in situ hybridization (FISH)-based human epidermal growth factor receptor (HER)-2 status assessment using different algorithms (copy number or the HER-2/centromere enumerator probe 17 [CEP-17] ratio). We investigated the effects of FISH-based HER-2 status assessment and aneusomy 17 on responsiveness to neoadjuvant chemotherapy (NAC). ### Patients And Methods This prospective study recruited 152 patients with locally advanced breast cancer who underwent four-cycle weekly paclitaxel plus carboplatin without trastuzumab . ### results The pathologic complete remission (pCR) rate in the breast and axilla was 24.3% (95% confidence interval [CI], 17.7%-32.0%). Although HER-2 status, assessed by either HER-2/CEP-17 ratio-based FISH or copy number-based FISH, was a predictor of NAC sensitivity, ratio-assessed HER-2 status had a poorer performance in determining patients' responsiveness to NAC (p = .029). Patients who were not HER-2 amplified when assessed using the HER-2/CEP-17 ratio but were HER-2 amplified when assessed using copy number (~5%) were eventually proven to be responsive to NAC, with a pCR rate of 57% (95% CI, 18.4%-90.1%). In contrast, patients who were HER-2 amplified when assessed by the ratio but not HER-2 amplified when assessed using copy number (~3%) were completely irresponsive. Higher HER-2 copy numbers represented increasing chances of a pCR (adjusted odds ratio, 3.09; 95% CI, 1.35-7.08), with an apparent gene-dose effect (p for trend < .001). ### conclusion It is likely that HER-2 copy number but not the HER-2/CEP-17 ratio determines NAC sensitivity. Additional studies to validate our findings are warranted.

sentence: This prospective study recruited 152 patients with locally advanced breast cancer who underwent four-cycle weekly paclitaxel plus carboplatin without trastuzumab .
[["paclitaxel", "carboplatin", "POS"]]