| Literature DB >> 33788898 |
Rosa Rodriguez-Monguio1,2,3, Mahim Naveed2, Enrique Seoane-Vazquez4,5.
Abstract
BACKGROUND: Shortages of opioid analgesics are increasingly common, interfere with patient care and increase healthcare cost. This study characterized the incidence of shortages of opioid analgesics in the period 2015-2019 and evaluated potential predictors to forecast the risk of shortages.Entities:
Year: 2021 PMID: 33788898 PMCID: PMC8011730 DOI: 10.1371/journal.pone.0249274
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Shortages of opioids: Odds ratios estimates.
Fig 2Kendall’s tau correlation coefficients for predictors of shortages.
FDA approved opioid NDCs and shortages, 2015–2019.
| NDCs | % NDCs | FDA Shortages | % of NDC | % of FDA Shortages | p value | |
|---|---|---|---|---|---|---|
| 8,207 | 105 | 1.3% | ||||
| 877 | 37 | 4.2% | ||||
| 418 | 11 | 2.6% | ||||
| <0.001 | ||||||
| 5,726 | 69.8% | 104 | 1.8% | 99.0% | ||
| 762 | 9.3% | |||||
| 757 | 9.2% | 1 | 0.1% | 1.0% | ||
| 962 | 11.7% | |||||
| <0.001 | ||||||
| 4,881 | 59.5% | 16 | 0.3% | 15.2% | ||
| 2,289 | 27.9% | 89 | 3.9% | 84.8% | ||
| 1,037 | 12.6% | |||||
| 944 | 11.5% | 16 | 1.7% | 15.2% | 0.292 | |
| 4,734 | 57.7% | |||||
| 6,943 | 84.6% | 91 | 1.3% | 86.7% | 0.649 | |
| 597 | 7.3% | 0.007 | ||||
| <0.001 | ||||||
| 25 | 0.3% | |||||
| 137 | 1.7% | |||||
| 67 | 0.8% | |||||
| 1340 | 16.3% | |||||
| 123 | 1.5% | |||||
| 275 | 3.4% | |||||
| 979 | 11.9% | 21 | 2.1% | 20.0% | ||
| 4 | 0.0% | |||||
| 1276 | 15.5% | |||||
| 27 | 0.3% | |||||
| 2 | 0.0% | |||||
| 604 | 7.4% | 31 | 5.1% | 29.5% | ||
| 260 | 3.2% | 1 | 0.4% | 1.0% | ||
| 118 | 1.4% | 2 | 1.7% | 1.9% | ||
| 1131 | 13.8% | 43 | 3.8% | 41.0% | ||
| 7 | 0.1% | |||||
| 24 | 0.3% | |||||
| 5 | 0.1% | |||||
| 35 | 0.4% | |||||
| 596 | 7.3% | |||||
| 13 | 0.2% | 1 | 7.7% | 1.0% | ||
| 19 | 0.2% | 6 | 31.6% | 5.7% | ||
| 93 | 1.1% | |||||
| 248 | 3.0% | |||||
| 799 | 9.7% | |||||
| <0.001 | ||||||
| 351 | 4.3% | 3 | 0.9% | 2.9% | ||
| 231 | 2.8% | 37 | 16.0% | 35.2% | ||
| 154 | 1.9% | |||||
| 146 | 1.8% | 5 | 3.4% | 4.8% | ||
| 150 | 1.8% | |||||
| 124 | 1.5% | |||||
| 98 | 1.2% | 9 | 9.2% | 8.6% | ||
| 92 | 1.1% | 12 | 13.0% | 11.4% | ||
| 55 | 0.7% | 23 | 41.8% | 21.9% | ||
| 60 | 0.7% | 9 | 15.0% | 8.6% | ||
| 6,365 | 77.6% | |||||
| 0.6 (0.2, 3.3) | 2.9 (1.2, 4.3) | <0.001 | ||||
| 62.5 (22.9, 239.7) | 82.7 (30.7, 170.0) | 0.05 | ||||
| 481 | 5.9% | |||||
| 2.0 (1.0, 4.0) | 8.0 (3.0, 13.0) | <0.001 | ||||
| 6.0 (2.0, 18.0) | 42.0 (11.0, 54.5) | 0.005 |
Injectable included injection, epidural, intramuscular, intrathecal, intravenous. Other administration routes included buccal mucosa, nasal, oromuscular, rectal, subcutaneous, transdermal. Other active ingredient included benzohydrocodone, butarphanol tartrate, codeine, dezocine, difenoxin hydrochloride, dihydrocodeine bitartrate, levomethadyl acetate hydrochloride, levorphanol tartrate, nalbuphine hydrochloride, terephthalate, oxymorphone hydrochloride, paregoric, pentazocine hydrochloride, propoxyphene hydrochloride, propoxyphene napsylate, tapentadol hydrochloride.
Opioid NDCs marketed and shortages, 2015–2019.
| NDCs | % NDC Marketed | % NDCs | p value | FDA Shortages | % NDC | % FDA Shortages | p value | |
|---|---|---|---|---|---|---|---|---|
| 3,017 | 36.8% | 91 | 3.0% | <0.001 | ||||
| 524 | 59.7% | 30 | 5.7% | |||||
| 183 | 43.8% | 9 | 4.9% | |||||
| <0.001 | <0.001 | |||||||
| 2,519 | 83.5% | 44.0% | 91 | 3.6% | 100.0% | |||
| 234 | 7.8% | 30.7% | ||||||
| 171 | 5.7% | 22.6% | ||||||
| 93 | 3.1% | 9.7% | ||||||
| <0.001 | <0.001 | |||||||
| 1,301 | 43.1% | 26.7% | 5 | 0.4% | 5.5% | |||
| 1,030 | 34.1% | 45.0% | 86 | 8.3% | 94.5% | |||
| 686 | 22.7% | 66.2% | ||||||
| 495 | 16.4% | 52.4% | <0.001 | 5 | 1.0% | 5.5% | 0.007 | |
| 1,155 | 38.3% | 31.8% | <0.001 | |||||
| 2,690 | 89.2% | 38.7% | <0.001 | 84 | 3.1% | 92.3% | 0.418 | |
| 270 | 8.9% | 45.2% | <0.001 | 0.004 | ||||
| <0.001 | <0.001 | |||||||
| 11 | 0.4% | 44.0% | ||||||
| 121 | 4.0% | 88.3% | ||||||
| 48 | 1.6% | 71.6% | ||||||
| 144 | 4.8% | 10.7% | ||||||
| 20 | 0.7% | 16.3% | ||||||
| 196 | 6.5% | 71.3% | ||||||
| 563 | 18.7% | 57.5% | 19 | 3.4% | 20.9% | |||
| 417 | 13.8% | 32.7% | ||||||
| 12 | 0.4% | 44.4% | ||||||
| 314 | 10.4% | 52.0% | 31 | 9.9% | 34.1% | |||
| 73 | 2.4% | 28.1% | 1 | 1.4% | 1.1% | |||
| 77 | 2.6% | 65.3% | 2 | 2.6% | 2.2% | |||
| 390 | 12.9% | 34.5% | 32 | 8.2% | 35.2% | |||
| 7 | 0.2% | 29.2% | ||||||
| 5 | 0.2% | 100.0% | ||||||
| 283 | 9.4% | 47.5% | ||||||
| 15 | 0.5% | 78.9% | 6 | 40.0% | 6.6% | |||
| 42 | 1.4% | 45.2% | ||||||
| 144 | 4.8% | 58.1% | ||||||
| 135 | 4.5% | 16.9% | ||||||
| <0.001 | <0.001 | |||||||
| 113 | 3.7% | 32.2% | 3 | 3.3% | 2.7% | |||
| 125 | 4.1% | 54.1% | 35 | 38.5% | 28.0% | |||
| 143 | 4.7% | 92.9% | ||||||
| 58 | 1.9% | 39.7% | ||||||
| 93 | 3.1% | 62.0% | ||||||
| 76 | 2.5% | 61.3% | ||||||
| 65 | 2.2% | 66.3% | 9 | 9.9% | 13.8% | |||
| 88 | 2.9% | 95.7% | 12 | 13.2% | 13.6% | |||
| 51 | 1.7% | 92.7% | 23 | 25.3% | 45.1% | |||
| 48 | 1.6% | 80.0% | 8 | 8.8% | 16.7% | |||
| 1882 | 62.4% | 29.6% | ||||||
| 1.5 (0.4,11.7) | <0.001 | 2.7 (1.2,3.6) | 0.106 | |||||
| 106.4 (32.0,513.1) | <0.001 | 75.7 (30.2,118.6) | 0.003 | |||||
| 426 | 14.1% | 88.6% | ||||||
| 1.0 (1.0, 3.0) | 3.0 (2.0,4.0) | <0.001 | ||||||
| 5.0 (2.0,15.5) | 22.0 (7.0,38.1) | 0.023 | ||||||
| 7.0 (3.0, 11.0) | <0.001 |
DEA schedule CII injectable opioid NDCs marketed and shortages, 2015–2019.
| NDCs | % CII injectable NDC Marketed | FDA Shortages | % FDA Shortages | % NDCs | p value | |
|---|---|---|---|---|---|---|
| 1,001 | 86 | 8.6% | <0.001 | |||
| 213 | 25 | 11.7% | ||||
| 16 | 8 | 50.0% | ||||
| 371 | 37.1% | |||||
| 961 | 96.0% | 79 | 91.9% | 8.2% | 0.078 | |
| 1 | 0.1% | |||||
| <0.001 | ||||||
| 11 | 1.1% | |||||
| 5 | 0.5% | |||||
| 480 | 48.0% | 19 | 22.1% | 4.0% | ||
| 236 | 23.6% | 31 | 36.0% | 13.1% | ||
| 45 | 4.5% | 1 | 1.2% | 2.2% | ||
| 8 | 0.8% | 2 | 2.3% | 25.0% | ||
| 175 | 17.5% | 27 | 31.4% | 15.4% | ||
| 15 | 1.5% | 6 | 7.0% | 40.0% | ||
| 26 | 2.6% | |||||
| <0.001 | ||||||
| 21 | 2.1% | 8 | 9.3% | 38.1% | ||
| 51 | 5.1% | 23 | 26.7% | 45.1% | ||
| 42 | 4.2% | 12 | 14.0% | 28.6% | ||
| 104 | 10.4% | 35 | 40.7% | 33.7% | ||
| 7 | 0.7% | 4 | 4.7% | 57.1% | ||
| 5 | 0.5% | 3 | 3.5% | 60.0% | ||
| 770 | 76.9% | |||||
| 0.3 (0.2, 0.8) | 2.6 (1.0, 3.4) | <0.001 | ||||
| 27.1 (16.6, 46.9) | 63.0 (30.0, 106.9) | <0.001 | ||||
| 89 | 8.9% | |||||
| 1.0 (1.0, 1.0) | 3.0 (2.0, 3.0) | <0.001 | ||||
| 15.0 (3.5, 36.0) | 18.0 (6.5, 37.2) | 0.495 | ||||
| 3.0 (0.0, 10.0) | 7.5 (2.8, 11.5) | 0.183 |
Multivariable logistic regression model for predicting risk of shortage of opioid analgesics.
| Covariates | Beta Estimate | Standard Error | Odds Ratio | Odds Ratio 95% Lower | Odds Ratio 95% Upper | P value |
|---|---|---|---|---|---|---|
| Intercept | -2.129 | 0.644 | 0.119 | 0.029 | 0.397 | 0.0009530 |
| Generics | 0.630 | 0.463 | 1.878 | 0.798 | 5.990 | 0.1730577 |
| # Companies per strength | 0.271 | 0.163 | 1.311 | 0.947 | 1.816 | 0.0966278 |
| # NDCs per company | -0.008 | 0.002 | 0.992 | 0.945 | 0.995 | 0.0000798 |
| Company risk | 0.034 | 0.012 | 1.034 | 1.011 | 1.283 | 0.0057170 |
Hosmer-Lemeshow Statistic p-value:0.95
McFadden pseudo R2: 0.46
Area Under Curve (95% CI):0.918(0.8868–0.9491)
ROC probability cut-off: 0.28