| Literature DB >> 35395002 |
Christine Jacomet1, Émilie Goncalves1, Céline Lambert2, Didier Chedorge3, Sylvia Puglièse-Wehrlen4, Éric Billaud5, David Zucman6, Anne Simon7, Cédric Arvieux8, Hervé Trout9, Bruno Laurandin10, René Maarek11, Isabelle Raymond12, Pascal Puglièse13, Julie Langlois14, Agnès Certain15.
Abstract
JUSTIFICATION: The WHO 95-95-95 targets for 2030 do not imply that people living with HIV (PLHIV) achieve a good quality of life. The current 30-day dispensing interval for antiretroviral (ART) burdens the healthcare system. Lengthening dispensing intervals could alleviate this burden as well as enhance patient well-being.Entities:
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Year: 2022 PMID: 35395002 PMCID: PMC8992981 DOI: 10.1371/journal.pone.0265166
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Patients on ART—Demographics and medical characteristics.
| PLHIV on ART | Patients on PrEP | ||
|---|---|---|---|
| (n = 999) | (n = 88) | ||
|
| Male | 654 (65.5%) | 88 (100.0%) |
| Female | 325 (32.5%) | 0 (0.0%) | |
| Trans female | 4 (0.4%) | 0 (0.0%) | |
| Trans male | 1 (0.1%) | 0 (0.0%) | |
| Declined | 1 (0.1%) | 0 (0.0%) | |
| Missing data | 14 (1.4%) | 0 (0.0%) | |
|
| IDF PACA ARA | 404 (40.4%) | 41 (46.6%) |
| DOM | 49 (4.9%) | 4 (4.5%) | |
| Other regions | 544 (54.5%) | 43 (48.9%) | |
| Missing data | 2 (0.2%) | 0 (0.0%) | |
|
| < 1 year | 34 (3.4%) | 29 (33.0%) |
| 1–10 years | 303 (30.3%) | 59 (67.0%) | |
| >10 years | 552 (55.3%) | 0 (0.0%) | |
| Missing data | 110 (11.0%) | 0 (0.0%) | |
|
| Undetectable < 6 months | 58 (5.8%) | N/A |
| Undetectable > 6 months | 854 (85.5%) | ||
| Detectable | 59 (5.9%) | ||
| Missing data | 28 (2.8%) | ||
|
| Hospital | 170 (17.0%) | 4 (4.6%) |
| Community pharmacy | 751 (75.2%) | 81 (92.0%) | |
| Both | 73 (7.3%) | 3 (3.4%) | |
| Missing data | 5 (0.5%) | 0 (0.0%) | |
|
| 1 pill a day | 687 (68.8%) | N/A |
| 2 pills taken once a day | 121 (12.1%) | ||
| 3 pills taken once a day | 123 (12.3%) | ||
| Pills taken more than once a day | 64 (6.4%) | ||
| Missing data | 4 (0.4%) | ||
|
| Daily | 955 (95.6%) | 59 (67.0%) |
| Structured interrupted | 35 (3.5%) | 29 (33.0%) | |
| Missing data | 9 (0.9%) | 0 (0.0%) |
ARA: Auvergne-Rhône-Alpes; ART: antiretroviral; DOM: French overseas; IDF: Île-de-France; N/A: does not apply; PACA: Provence-Alpes-Côte d’Azur.
a: IDF, PACA, ARA are region of high HIV prevalence in France.
Characteristics of the in-sample doctors and pharmacists.
| Doctors | Pharmacists | |||
|---|---|---|---|---|
| (n = 220) | (n = 176) | |||
|
| IDF PACA ARA | 93 (42.3%) | 71 (40.3%) | |
| DOM | 13 (5.9%) | 2 (1.1%) | ||
| Other regions | 112 (50.9%) | 102 (58.0%) | ||
| Missing data | 2 (0.9%) | 1 (0.6%) | ||
|
| University hospital | 153 (69.5%) | 24 (13.6%) | |
| General hospital | 62 (28.2%) | 11 (6.3%) | ||
| Community practice | 1 (0.5%) | 137 (77.8%) | ||
| Private hospital | 0 (0.0%) | 1 (0.6%) | ||
| Missing data | 4 (1.8%) | 3 (1.7%) | ||
|
| Doctors | <100 | 91 (41.4%) | NA |
| 100–500 | 114 (51.8%) | |||
| >500 | 12 (5.4%) | |||
| Missing data | 3 (1.4%) | |||
| Pharmacists | 0–2 | NA | 25 (14.2%) | |
| 2–30 | 106 (60.2%) | |||
| >30 | 35 (19.9%) | |||
| Missing data | 10 (5.7%) | |||
|
| Doctors | <30 | 153 (69.6%) | NA |
| 30–100 | 30 (13.6%) | |||
| >100 | 10 (4.5%) | |||
| Missing data | 27 (12.3%) | |||
| Pharmacists | 0–2 | NA | 82 (46.6%) | |
| 2–30 | 42 (23.9%) | |||
| >30 | 7 (4.0%) | |||
| Missing data | 45 (25.6%) |
ARA: Auvergne-Rhône-Alpes; DOM: French overseas; IDF: Île-de-France; PACA: Provence-Alpes-Côte d’Azur; PrEP: pre-exposure prophylaxis; PLHIV: persons living with HIV.
a: IDF, PACA, ARA are regions of high HIV prevalence in France.
b: the prevalence of pharmacists in France (32/100 000 habitants) is much higher than the prevalence of doctors involved in HIV and PrEP in 2020 (around 1/100 000).
Fig 1A. Comparison of the benefits of a 90-day ART dispensing interval reported by people on ART (PLHIV and people on PrEP) and their doctors and pharmacists. A = significant difference between doctors and pharmacists, B = significant difference between doctors and people on ART (PLHIV and people on PrEP), C = significant difference between pharmacists and people on ART (PLHIV and people on PrEP). B. Comparison of the limitations of a 90-day ART dispensing interval reported by people on ART (PLHIV and people on PrEP) and their doctors and pharmacists. A = significant difference between doctors and pharmacists, B = significant difference between doctors and people on ART (PLHIV and people on PrEP), C = significant difference between pharmacists and people on ART (PLHIV and people on PrEP).
Characteristics of in-sample PLHIV and in-sample people on PrEP stratified as endorsers vs non-endorsers of 90-day ART dispensing (n = 1074).
| Total PLHIV and people on PrEP | Endorsers | Non-endorsers |
| ||
|---|---|---|---|---|---|
| (n = 1074) | (n = 925) | (n = 149) | |||
|
| Male | 738 (68.7%) | 629 (68.0%) | 109 (73.1%) | 0.21 |
| Female | 323 (30.1%) | 285 (30.8%) | 38 (25.5%) | ||
| Trans female | 4 (0.4%) | 4 (0.4%) | 0 (0.0%) | ||
| Trans male | 1 (0.1%) | 0 (0.0%) | 1 (0.7%) | ||
| Refuses to self-identify | 1 (0.1%) | 1 (0.1%) | 0 (0.0%) | ||
| Missing data | 7 (0.6%) | 6 (0.7%) | 1 (0.7%) | ||
|
| IDF PACA ARA | 439 (40.9%) | 391 (42.3%) | 48 (32.2%) | 0.004 |
| DOM | 53 (4.9%) | 46 (5.0%) | 7 (4.7%) | ||
| Other regions | 580 (54.0%) | 488 (52.7%) | 92 (61.7%) | ||
| Missing data | 2 (0.2%) | 0 (0.0%) | 2 (1.4%) | ||
|
| < 1 year | 62 (5.8%) | 52 (5.6%) | 10 (6.7%) | 0.31 |
| 1–10 years | 358 (33.3%) | 313 (33.8%) | 45 (30.2%) | ||
| >10 years | 547 (50.9%) | 463 (50.1%) | 84 (56.4%) | ||
| Missing data | 107 (10.0%) | 97 (10.5%) | 10 (6.7%) | ||
|
| Undetectable < 6 months | 58 (5.4%) | 47 (5.1%) | 11 (7.4%) | 0.13 |
| Undetectable > 6 months | 853 (79.4%) | 746 (80.6%) | 107 (71.8%) | ||
| Detectable | 59 (5.5%) | 47 (5.1%) | 12 (8.1%) | ||
| N/A | 86 (8.0%) | 70 (7.6%) | 16 (10.7%) | ||
| Missing data | 18 (1.7%) | 15 (1.6%) | 3 (2.0%) | ||
|
| Hospital | 173 (16.1%) | 164 (17.7%) | 9 (6.0%) | <0.001 |
| Community pharmacy | 821 (76.4%) | 686 (74.2%) | 135 (90.6%) | ||
| Both | 75 (7.0%) | 70 (7.6%) | 5 (3.4%) | ||
| Missing data | 5 (0.5%) | 5 (0.5%) | 0 (0.0%) | ||
|
| 1 pill a day | 757 (70.5%) | 669 (72.3%) | 88 (59.1%) | 0.004 |
| 2 pills taken once a day | 124 (11.5%) | 99 (10.7%) | 25 (16.8%) | ||
| 3 pills taken once a day | 123 (11.4%) | 103 (11.2%) | 20 (13.4%) | ||
| Pills taken more than once a day | 63 (5.9%) | 50 (5.4%) | 13 (8.7%) | ||
| Missing data | 7 (0.7%) | 4 (0.4%) | 3 (2.0%) | ||
|
| Daily | 1002 (93.3%) | 865 (93.5%) | 137 (91.9%) | 0.70 |
| Structured interrupted | 64 (6.0%) | 53 (5.7%) | 11 (7.4%) | ||
| Missing data | 8 (0.7%) | 7 (0.8%) | 1 (0.7%) | ||
|
| 1011 (94.1%) | 922 (99.7%) | 89 (59.7%) | <0.001 | |
| More convenient | 836 (82.7%) | 793 (86.0%) | 43 (48.3%) | <0.001 | |
| Less risk of end-of-month shortages | 519 (51.3%) | 480 (52.1%) | 39 (43.8%) | 0.14 | |
| More self-manageability | 408 (40.4%) | 391 (42.4%) | 17 (19.1%) | <0.001 | |
| Better quality of life | 262 (25.9%) | 256 (27.8%) | 6 (6.7%) | <0.001 | |
| Less expensive | 141 (13.9%) | 131 (14.2%) | 10 (11.2%) | 0.44 | |
| More privacy | 299 (29.6%) | 287 (31.1%) | 12 (13.5%) | <0.001 | |
| Other | 54 (5.3%) | 50 (5.4%) | 4 (4.5%) | 1.00 | |
|
| 555 (51.7%) | 440 (47.6%) | 115 (77.2%) | <0.001 | |
| Regulatory complexity | 118 (21.3%) | 106 (24.1%) | 12 (10.4%) | 0.001 | |
| Anxiety over access to dispensing if doses get lost | 190 (34.2%) | 155 (35.2%) | 35 (30.4%) | 0.34 | |
| Insecurity around less access to supportive services | 55 (9.9%) | 33 (7.5%) | 22 (19.1%) | <0.001 | |
| Risk of running out of stock | 194 (35.0%) | 169 (38.4%) | 25 (21.7%) | 0.001 | |
| Too much stock at home | 154 (27.7%) | 82 (18.6%) | 72 (62.6%) | <0.001 | |
| More expensive | 27 (4.9%) | 22 (5.0%) | 5 (4.3%) | 0.77 | |
ARA: Auvergne-Rhône-Alpes; ART: antiretroviral; DOM: French overseas; IDF: Île-de-France; N/A: does not apply; PACA: Provence-Alpes-Côte d’Azur; PrEP: pre-exposure prophylaxis; PLHIV: persons living with HIV.
a: IDF, PACA, ARA are regions of high HIV prevalence in France.
b: people who do not endorse a change in model or have no preference.
Fig 2Characteristics of in-sample PLHIV and in-sample people on PrEP stratified as endorsers vs non-endorsers of 90-day ART dispensing (n = 1074).
Multivariate analysis. ARA: Auvergne-Rhône-Alpes; ART: antiretroviral; DOM: French overseas; IDF: Île-de-France; N/A: does not apply; PACA: Provence-Alpes-Côte d’Azur. IDF, PACA, ARA are regions of high HIV prevalence in France.
Characteristics of the 219 doctors endorsing 90-day dispensing of ART for all vs only for people with eligible therapeutic criteria and with good immune and virological factors and/or favourable social issues.
| Total | 90-day dispensing for all | 90-day dispensing for people with specific factors/issues |
| ||
|---|---|---|---|---|---|
| (n = 219) | (n = 42) | (n = 177) | |||
|
| IDF PACA ARA | 93 (42.5%) | 18 (42.9%) | 75 (42.4%) | 0.93 |
| DOM | 13 (5.9%) | 3 (7.1%) | 10 (5.6%) | ||
| Other regions | 111 (50.7%) | 21 (50.0%) | 90 (50.9%) | ||
| Missing data | 2 (0.9%) | 0 (0.0%) | 2 (1.1%) | ||
|
| University hospital | 152 (69.4%) | 26 (61.9%) | 126 (71.2%) | 0.07 |
| General hospital | 62 (28.3%) | 13 (30.9%) | 49 (27.7%) | ||
| Community practice | 1 (0.5%) | 1 (2.4%) | 0 (0.0%) | ||
| Missing data | 4 (1.8%) | 2 (4.8%) | 2 (1.1%) | ||
|
| < 100 | 91 (41.5%) | 13 (31.0%) | 78 (44.1%) | 0.005 |
| 100–500 | 113 (51.6%) | 22 (52.4%) | 91 (51.4%) | ||
| > 500 | 12 (5.5%) | 4 (9.5%) | 8 (4.5%) | ||
| Missing data | 3 (1.4%) | 3 (7.1%) | 0 (0.0%) | ||
|
| < 30 | 152 (69.4%) | 31 (73.8%) | 121 (68.4%) | 0.22 |
| 30–100 | 30 (13.7%) | 2 (4.8%) | 28 (15.8%) | ||
| > 100 | 10 (4.6%) | 2 (4.8%) | 8 (4.5%) | ||
| Missing data | 27 (12.3%) | 7 (16.7%) | 20 (11.3%) |
ARA: Auvergne-Rhône-Alpes; DOM: French overseas; IDF: Île-de-France; PACA: Provence-Alpes-Côte d’Azur; PrEP: pre-exposure prophylaxis; PLHIV: persons living with HIV.
a: IDF, PACA, ARA are regions of high HIV prevalence in France.
Comparative analysis of responses from doctors and pharmacists concerning eligibility therapeutic, immunovirologic, or social conditions for 90-day ART dispensing.
| Doctors | Pharmacists |
| |
|---|---|---|---|
| (n = 220) | (n = 176) | ||
| Positive endorsement of 90-day dispensing | 219 (99.5%) | 152 (86.4%) | <0.001 |
| If the patient is a registered client | N/A | 13/152 (8.5%) | N/A |
| Without criteria | 42/219 (19.2%) | 8/152 (5.3%) | <0.001 |
|
|
|
| 0.18 |
| regardless of ART regimen | 112 (50.9%) | 55 (31.3%) | <0.001 |
| only if therapy is one pill a day | 6 (2.7%) | 14 (8.0%) | 0.02 |
| if the therapy regimen is continuous | 41 (18.6%) | 66 (37.5%) | <0.001 |
| if patient has been stable on the therapy more than 6 months | 59 (26.8%) | 52 (29.5%) | 0.55 |
| if viral load is undetectable and CD4 > 500 | 36 (16.4%) | 17 (9.7%) | 0.052 |
| if adherence to therapy is good | 52 (23.6%) | 41 (23.3%) | 0.94 |
| if therapy was initiated more than 6 months ago and there is undetectable viral load | 101 (45.9%) | 46 (26.1%) | <0.001 |
| regardless of the patient’s social factors | 35 (15.9%) | 47 (26.7%) | 0.008 |
| if the patient’s social factors appear to be stable | 99 (45.0%) | 51 (29.0%) | 0.001 |
| on demand, regardless of the patient’s social factors | 38 (17.3%) | 20 (11.4%) | 0.10 |
ART: antiretrovirals; N/A: does not apply.
a This question was only put to pharmacists who were, in 2020, more numerous in France than doctors in charge of HIV and PrEP. A patient can go to any pharmacy to receive his or her ART, including a distant pharmacy to avoid stigmatization.
b Social factors: housing, health insurance, resident permit.